Struct Traj

pub struct Traj<S: Interpolatable>
where
    DefaultAllocator: Allocator<S::VecLength> + Allocator<S::Size> + Allocator<S::Size, S::Size>,
{
    pub name: Option<String>,
    pub states: Vec<S>,
}

Store a trajectory of any State.

Fields

name: Option<String>

Optionally name this trajectory

states: Vec<S>

We use a vector because we know that the states are produced in a chronological manner (the direction does not matter).

Implementations

impl Traj<Spacecraft>

pub fn from_bsp( target_frame: Frame, observer_frame: Frame, almanac: Arc<Almanac>, sc_template: Spacecraft, step: Duration, start_epoch: Option<Epoch>, end_epoch: Option<Epoch>, ab_corr: Option<Aberration>, name: Option<String>, ) -> Result<Self, AlmanacError>

Builds a new trajectory built from the SPICE BSP (SPK) file loaded in the provided Almanac, provided the start and stop epochs.

If the start and stop epochs are not provided, then the full domain of the trajectory will be used.

Examples found in repository

examples/04_lro_od/main.rs (lines 92-102)

fn main() -> Result<(), Box<dyn Error>> {
    pel::init();

    // ====================== //
    // === ALMANAC SET UP === //
    // ====================== //

    // Dynamics models require planetary constants and ephemerides to be defined.
    // Let's start by grabbing those by using ANISE's MetaAlmanac.

    let data_folder: PathBuf = [env!("CARGO_MANIFEST_DIR"), "examples", "04_lro_od"]
        .iter()
        .collect();

    let meta = data_folder.join("lro-dynamics.dhall");

    // Load this ephem in the general Almanac we're using for this analysis.
    let mut almanac = MetaAlmanac::new(meta.to_string_lossy().to_string())
        .map_err(Box::new)?
        .process(true)
        .map_err(Box::new)?;

    let mut moon_pc = almanac.planetary_data.get_by_id(MOON)?;
    moon_pc.mu_km3_s2 = 4902.74987;
    almanac.planetary_data.set_by_id(MOON, moon_pc)?;

    let mut earth_pc = almanac.planetary_data.get_by_id(EARTH)?;
    earth_pc.mu_km3_s2 = 398600.436;
    almanac.planetary_data.set_by_id(EARTH, earth_pc)?;

    // Save this new kernel for reuse.
    // In an operational context, this would be part of the "Lock" process, and should not change throughout the mission.
    almanac
        .planetary_data
        .save_as(&data_folder.join("lro-specific.pca"), true)?;

    // Lock the almanac (an Arc is a read only structure).
    let almanac = Arc::new(almanac);

    // Orbit determination requires a Trajectory structure, which can be saved as parquet file.
    // In our case, the trajectory comes from the BSP file, so we need to build a Trajectory from the almanac directly.
    // To query the Almanac, we need to build the LRO frame in the J2000 orientation in our case.
    // Inspecting the LRO BSP in the ANISE GUI shows us that NASA has assigned ID -85 to LRO.
    let lro_frame = Frame::from_ephem_j2000(-85);

    // To build the trajectory we need to provide a spacecraft template.
    let sc_template = Spacecraft::builder()
        .dry_mass_kg(1018.0) // Launch masses
        .fuel_mass_kg(900.0)
        .srp(SrpConfig {
            // SRP configuration is arbitrary, but we will be estimating it anyway.
            area_m2: 3.9 * 2.7,
            cr: 0.96,
        })
        .orbit(Orbit::zero(MOON_J2000)) // Setting a zero orbit here because it's just a template
        .build();
    // Now we can build the trajectory from the BSP file.
    // We'll arbitrarily set the tracking arc to 48 hours with a one minute time step.
    let traj_as_flown = Traj::from_bsp(
        lro_frame,
        MOON_J2000,
        almanac.clone(),
        sc_template,
        5.seconds(),
        Some(Epoch::from_str("2024-01-01 00:00:00 UTC")?),
        Some(Epoch::from_str("2024-01-02 00:00:00 UTC")?),
        Aberration::LT,
        Some("LRO".to_string()),
    )?;

    println!("{traj_as_flown}");

    // ====================== //
    // === MODEL MATCHING === //
    // ====================== //

    // Set up the spacecraft dynamics.

    // Specify that the orbital dynamics must account for the graviational pull of the Earth and the Sun.
    // The gravity of the Moon will also be accounted for since the spaceraft in a lunar orbit.
    let mut orbital_dyn = OrbitalDynamics::point_masses(vec![EARTH, SUN, JUPITER_BARYCENTER]);

    // We want to include the spherical harmonics, so let's download the gravitational data from the Nyx Cloud.
    // We're using the GRAIL JGGRX model.
    let mut jggrx_meta = MetaFile {
        uri: "http://public-data.nyxspace.com/nyx/models/Luna_jggrx_1500e_sha.tab.gz".to_string(),
        crc32: Some(0x6bcacda8), // Specifying the CRC32 avoids redownloading it if it's cached.
    };
    // And let's download it if we don't have it yet.
    jggrx_meta.process(true)?;

    // Build the spherical harmonics.
    // The harmonics must be computed in the body fixed frame.
    // We're using the long term prediction of the Moon principal axes frame.
    let moon_pa_frame = MOON_PA_FRAME.with_orient(31008);
    // let moon_pa_frame = IAU_MOON_FRAME;
    let sph_harmonics = Harmonics::from_stor(
        almanac.frame_from_uid(moon_pa_frame)?,
        HarmonicsMem::from_shadr(&jggrx_meta.uri, 80, 80, true)?,
    );

    // Include the spherical harmonics into the orbital dynamics.
    orbital_dyn.accel_models.push(sph_harmonics);

    // We define the solar radiation pressure, using the default solar flux and accounting only
    // for the eclipsing caused by the Earth and Moon.
    // Note that by default, enabling the SolarPressure model will also enable the estimation of the coefficient of reflectivity.
    let srp_dyn = SolarPressure::new(vec![EARTH_J2000, MOON_J2000], almanac.clone())?;

    // Finalize setting up the dynamics, specifying the force models (orbital_dyn) separately from the
    // acceleration models (SRP in this case). Use `from_models` to specify multiple accel models.
    let dynamics = SpacecraftDynamics::from_model(orbital_dyn, srp_dyn);

    println!("{dynamics}");

    // Now we can build the propagator.
    let setup = Propagator::default_dp78(dynamics.clone());

    // For reference, let's build the trajectory with Nyx's models from that LRO state.
    let (sim_final, traj_as_sim) = setup
        .with(*traj_as_flown.first(), almanac.clone())
        .until_epoch_with_traj(traj_as_flown.last().epoch())?;

    println!("SIM INIT:  {:x}", traj_as_flown.first());
    println!("SIM FINAL: {sim_final:x}");
    // Compute RIC difference between SIM and LRO ephem
    let sim_lro_delta = sim_final
        .orbit
        .ric_difference(&traj_as_flown.last().orbit)?;
    println!("{traj_as_sim}");
    println!(
        "SIM v LRO - RIC Position (m): {:.3}",
        sim_lro_delta.radius_km * 1e3
    );
    println!(
        "SIM v LRO - RIC Velocity (m/s): {:.3}",
        sim_lro_delta.velocity_km_s * 1e3
    );

    traj_as_sim.ric_diff_to_parquet(
        &traj_as_flown,
        "./04_lro_sim_truth_error.parquet",
        ExportCfg::default(),
    )?;

    // ==================== //
    // === OD SIMULATOR === //
    // ==================== //

    // After quite some time trying to exactly match the model, we still end up with an oscillatory difference on the order of 150 meters between the propagated state
    // and the truth LRO state.

    // Therefore, we will actually run an estimation from a dispersed LRO state.
    // The sc_seed is the true LRO state from the BSP.
    let sc_seed = *traj_as_flown.first();

    // Load the Deep Space Network ground stations.
    // Nyx allows you to build these at runtime but it's pretty static so we can just load them from YAML.
    let ground_station_file: PathBuf = [
        env!("CARGO_MANIFEST_DIR"),
        "examples",
        "04_lro_od",
        "dsn-network.yaml",
    ]
    .iter()
    .collect();

    let devices = GroundStation::load_many(ground_station_file)?;

    // Typical OD software requires that you specify your own tracking schedule or you'll have overlapping measurements.
    // Nyx can build a tracking schedule for you based on the first station with access.
    let trkconfg_yaml: PathBuf = [
        env!("CARGO_MANIFEST_DIR"),
        "examples",
        "04_lro_od",
        "tracking-cfg.yaml",
    ]
    .iter()
    .collect();

    let configs: BTreeMap<String, TrkConfig> = TrkConfig::load_named(trkconfg_yaml)?;

    // Build the tracking arc simulation to generate a "standard measurement".
    let mut trk = TrackingArcSim::<Spacecraft, RangeDoppler, _>::new(
        devices,
        traj_as_flown.clone(),
        configs,
    )?;

    trk.build_schedule(almanac.clone())?;
    let arc = trk.generate_measurements(almanac.clone())?;
    // Save the simulated tracking data
    arc.to_parquet_simple("./04_lro_simulated_tracking.parquet")?;

    // We'll note that in our case, we have continuous coverage of LRO when the vehicle is not behind the Moon.
    println!("{arc}");

    // Now that we have simulated measurements, we'll run the orbit determination.

    // ===================== //
    // === OD ESTIMATION === //
    // ===================== //

    let sc = SpacecraftUncertainty::builder()
        .nominal(sc_seed)
        .frame(LocalFrame::RIC)
        .x_km(0.5)
        .y_km(0.5)
        .z_km(0.5)
        .vx_km_s(5e-3)
        .vy_km_s(5e-3)
        .vz_km_s(5e-3)
        .build();

    // Build the filter initial estimate, which we will reuse in the filter.
    let initial_estimate = sc.to_estimate()?;

    println!("== FILTER STATE ==\n{sc_seed:x}\n{initial_estimate}");

    let kf = KF::new(
        // Increase the initial covariance to account for larger deviation.
        initial_estimate,
        // Until https://github.com/nyx-space/nyx/issues/351, we need to specify the SNC in the acceleration of the Moon J2000 frame.
        SNC3::from_diagonal(10 * Unit::Minute, &[1e-11, 1e-11, 1e-11]),
    );

    // We'll set up the OD process to reject measurements whose residuals are mover than 4 sigmas away from what we expect.
    let mut odp = ODProcess::ckf(
        setup.with(initial_estimate.state().with_stm(), almanac.clone()),
        kf,
        Some(ResidRejectCrit::default()),
        almanac.clone(),
    );

    odp.process_arc::<GroundStation>(&arc)?;

    let ric_err = traj_as_flown
        .at(odp.estimates.last().unwrap().epoch())?
        .orbit
        .ric_difference(&odp.estimates.last().unwrap().orbital_state())?;
    println!("== RIC at end ==");
    println!("RIC Position (m): {}", ric_err.radius_km * 1e3);
    println!("RIC Velocity (m/s): {}", ric_err.velocity_km_s * 1e3);

    odp.to_parquet("./04_lro_od_results.parquet", ExportCfg::default())?;

    // In our case, we have the truth trajectory from NASA.
    // So we can compute the RIC state difference between the real LRO ephem and what we've just estimated.
    // Export the OD trajectory first.
    let od_trajectory = odp.to_traj()?;
    // Build the RIC difference.
    od_trajectory.ric_diff_to_parquet(
        &traj_as_flown,
        "./04_lro_od_truth_error.parquet",
        ExportCfg::default(),
    )?;

    Ok(())
}

pub fn to_frame( &self, new_frame: Frame, almanac: Arc<Almanac>, ) -> Result<Self, NyxError>

Allows converting the source trajectory into the (almost) equivalent trajectory in another frame

pub fn to_parquet_with_step<P: AsRef<Path>>( &self, path: P, step: Duration, almanac: Arc<Almanac>, ) -> Result<(), Box<dyn Error>>

A shortcut to to_parquet_with_cfg

pub fn to_groundtrack_parquet<P: AsRef<Path>>( &self, path: P, body_fixed_frame: Frame, events: Option<Vec<&dyn EventEvaluator<Spacecraft>>>, metadata: Option<HashMap<String, String>>, almanac: Arc<Almanac>, ) -> Result<PathBuf, Box<dyn Error>>

Exports this trajectory to the provided filename in parquet format with only the epoch, the geodetic latitude, longitude, and height at one state per minute. Must provide a body fixed frame to correctly compute the latitude and longitude.

pub fn from_oem_file<P: AsRef<Path>>( path: P, tpl_option: Option<Spacecraft>, ) -> Result<Self, NyxError>

Initialize a new spacecraft trajectory from the path to a CCSDS OEM file.

CCSDS OEM only contains the orbit information but Nyx builds spacecraft trajectories. If not spacecraft template is provided, then a default massless spacecraft will be built.

pub fn to_oem_file<P: AsRef<Path>>( &self, path: P, cfg: ExportCfg, ) -> Result<PathBuf, NyxError>

Examples found in repository

examples/01_orbit_prop/main.rs (lines 178-181)

fn main() -> Result<(), Box<dyn Error>> {
    pel::init();
    // Dynamics models require planetary constants and ephemerides to be defined.
    // Let's start by grabbing those by using ANISE's latest MetaAlmanac.
    // This will automatically download the DE440s planetary ephemeris,
    // the daily-updated Earth Orientation Parameters, the high fidelity Moon orientation
    // parameters (for the Moon Mean Earth and Moon Principal Axes frames), and the PCK11
    // planetary constants kernels.
    // For details, refer to https://github.com/nyx-space/anise/blob/master/data/latest.dhall.
    // Note that we place the Almanac into an Arc so we can clone it cheaply and provide read-only
    // references to many functions.
    let almanac = Arc::new(MetaAlmanac::latest().map_err(Box::new)?);
    // Define the orbit epoch
    let epoch = Epoch::from_gregorian_utc_hms(2024, 2, 29, 12, 13, 14);

    // Define the orbit.
    // First we need to fetch the Earth J2000 from information from the Almanac.
    // This allows the frame to include the gravitational parameters and the shape of the Earth,
    // defined as a tri-axial ellipoid. Note that this shape can be changed manually or in the Almanac
    // by loading a different set of planetary constants.
    let earth_j2000 = almanac.frame_from_uid(EARTH_J2000)?;

    let orbit =
        Orbit::try_keplerian_altitude(300.0, 0.015, 68.5, 65.2, 75.0, 0.0, epoch, earth_j2000)?;
    // Print in in Keplerian form.
    println!("{orbit:x}");

    // There are two ways to propagate an orbit. We can make a quick approximation assuming only two-body
    // motion. This is a useful first order approximation but it isn't used in real-world applications.

    // This approach is a feature of ANISE.
    let future_orbit_tb = orbit.at_epoch(epoch + Unit::Day * 3)?;
    println!("{future_orbit_tb:x}");

    // Two body propagation relies solely on Kepler's laws, so only the true anomaly will change.
    println!(
        "SMA changed by {:.3e} km",
        orbit.sma_km()? - future_orbit_tb.sma_km()?
    );
    println!(
        "ECC changed by {:.3e}",
        orbit.ecc()? - future_orbit_tb.ecc()?
    );
    println!(
        "INC changed by {:.3e} deg",
        orbit.inc_deg()? - future_orbit_tb.inc_deg()?
    );
    println!(
        "RAAN changed by {:.3e} deg",
        orbit.raan_deg()? - future_orbit_tb.raan_deg()?
    );
    println!(
        "AOP changed by {:.3e} deg",
        orbit.aop_deg()? - future_orbit_tb.aop_deg()?
    );
    println!(
        "TA changed by {:.3} deg",
        orbit.ta_deg()? - future_orbit_tb.ta_deg()?
    );

    // Nyx is used for high fidelity propagation, not Keplerian propagation as above.
    // Nyx only propagates Spacecraft at the moment, which allows it to account for acceleration
    // models such as solar radiation pressure.

    // Let's build a cubesat sized spacecraft, with an SRP area of 10 cm^2 and a mass of 9.6 kg.
    let sc = Spacecraft::builder()
        .orbit(orbit)
        .dry_mass_kg(9.60)
        .srp(SrpConfig {
            area_m2: 10e-4,
            cr: 1.1,
        })
        .build();
    println!("{sc:x}");

    // Set up the spacecraft dynamics.

    // Specify that the orbital dynamics must account for the graviational pull of the Moon and the Sun.
    // The gravity of the Earth will also be accounted for since the spaceraft in an Earth orbit.
    let mut orbital_dyn = OrbitalDynamics::point_masses(vec![MOON, SUN]);

    // We want to include the spherical harmonics, so let's download the gravitational data from the Nyx Cloud.
    // We're using the JGM3 model here, which is the default in GMAT.
    let mut jgm3_meta = MetaFile {
        uri: "http://public-data.nyxspace.com/nyx/models/JGM3.cof.gz".to_string(),
        crc32: Some(0xF446F027), // Specifying the CRC32 avoids redownloading it if it's cached.
    };
    // And let's download it if we don't have it yet.
    jgm3_meta.process(true)?;

    // Build the spherical harmonics.
    // The harmonics must be computed in the body fixed frame.
    // We're using the long term prediction of the Earth centered Earth fixed frame, IAU Earth.
    let harmonics_21x21 = Harmonics::from_stor(
        almanac.frame_from_uid(IAU_EARTH_FRAME)?,
        HarmonicsMem::from_cof(&jgm3_meta.uri, 21, 21, true).unwrap(),
    );

    // Include the spherical harmonics into the orbital dynamics.
    orbital_dyn.accel_models.push(harmonics_21x21);

    // We define the solar radiation pressure, using the default solar flux and accounting only
    // for the eclipsing caused by the Earth.
    let srp_dyn = SolarPressure::default(EARTH_J2000, almanac.clone())?;

    // Finalize setting up the dynamics, specifying the force models (orbital_dyn) separately from the
    // acceleration models (SRP in this case). Use `from_models` to specify multiple accel models.
    let dynamics = SpacecraftDynamics::from_model(orbital_dyn, srp_dyn);

    println!("{dynamics}");

    // Finally, let's propagate this orbit to the same epoch as above.
    // The first returned value is the spacecraft state at the final epoch.
    // The second value is the full trajectory where the step size is variable step used by the propagator.
    let (future_sc, trajectory) = Propagator::default(dynamics)
        .with(sc, almanac.clone())
        .until_epoch_with_traj(future_orbit_tb.epoch)?;

    println!("=== High fidelity propagation ===");
    println!(
        "SMA changed by {:.3} km",
        orbit.sma_km()? - future_sc.orbit.sma_km()?
    );
    println!(
        "ECC changed by {:.6}",
        orbit.ecc()? - future_sc.orbit.ecc()?
    );
    println!(
        "INC changed by {:.3e} deg",
        orbit.inc_deg()? - future_sc.orbit.inc_deg()?
    );
    println!(
        "RAAN changed by {:.3} deg",
        orbit.raan_deg()? - future_sc.orbit.raan_deg()?
    );
    println!(
        "AOP changed by {:.3} deg",
        orbit.aop_deg()? - future_sc.orbit.aop_deg()?
    );
    println!(
        "TA changed by {:.3} deg",
        orbit.ta_deg()? - future_sc.orbit.ta_deg()?
    );

    // We also have access to the full trajectory throughout the propagation.
    println!("{trajectory}");

    // With the trajectory, let's build a few data products.

    // 1. Export the trajectory as a CCSDS OEM version 2.0 file and as a parquet file, which includes the Keplerian orbital elements.

    trajectory.to_oem_file(
        "./01_cubesat_hf_prop.oem",
        ExportCfg::builder().step(Unit::Minute * 2).build(),
    )?;

    trajectory.to_parquet_with_cfg(
        "./01_cubesat_hf_prop.parquet",
        ExportCfg::builder().step(Unit::Minute * 2).build(),
        almanac.clone(),
    )?;

    // 2. Compare the difference in the radial-intrack-crosstrack frame between the high fidelity
    // and Keplerian propagation. The RIC frame is commonly used to compute the difference in position
    // and velocity of different spacecraft.
    // 3. Compute the azimuth, elevation, range, and range-rate data of that spacecraft as seen from Boulder, CO, USA.

    let boulder_station = GroundStation::from_point(
        "Boulder, CO, USA".to_string(),
        40.014984,   // latitude in degrees
        -105.270546, // longitude in degrees
        1.6550,      // altitude in kilometers
        almanac.frame_from_uid(IAU_EARTH_FRAME)?,
    );

    // We iterate over the trajectory, grabbing a state every two minutes.
    let mut offset_s = vec![];
    let mut epoch_str = vec![];
    let mut ric_x_km = vec![];
    let mut ric_y_km = vec![];
    let mut ric_z_km = vec![];
    let mut ric_vx_km_s = vec![];
    let mut ric_vy_km_s = vec![];
    let mut ric_vz_km_s = vec![];

    let mut azimuth_deg = vec![];
    let mut elevation_deg = vec![];
    let mut range_km = vec![];
    let mut range_rate_km_s = vec![];
    for state in trajectory.every(Unit::Minute * 2) {
        // Try to compute the Keplerian/two body state just in time.
        // This method occasionally fails to converge on an appropriate true anomaly
        // from the mean anomaly. If that happens, we just skip this state.
        // The high fidelity and Keplerian states diverge continuously, and we're curious
        // about the divergence in this quick analysis.
        let this_epoch = state.epoch();
        match orbit.at_epoch(this_epoch) {
            Ok(tb_then) => {
                offset_s.push((this_epoch - orbit.epoch).to_seconds());
                epoch_str.push(format!("{this_epoch}"));
                // Compute the two body state just in time.
                let ric = state.orbit.ric_difference(&tb_then)?;
                ric_x_km.push(ric.radius_km.x);
                ric_y_km.push(ric.radius_km.y);
                ric_z_km.push(ric.radius_km.z);
                ric_vx_km_s.push(ric.velocity_km_s.x);
                ric_vy_km_s.push(ric.velocity_km_s.y);
                ric_vz_km_s.push(ric.velocity_km_s.z);

                // Compute the AER data for each state.
                let aer = almanac.azimuth_elevation_range_sez(
                    state.orbit,
                    boulder_station.to_orbit(this_epoch, &almanac)?,
                    None,
                    None,
                )?;
                azimuth_deg.push(aer.azimuth_deg);
                elevation_deg.push(aer.elevation_deg);
                range_km.push(aer.range_km);
                range_rate_km_s.push(aer.range_rate_km_s);
            }
            Err(e) => warn!("{} {e}", state.epoch()),
        };
    }

    // Build the data frames.
    let ric_df = df!(
        "Offset (s)" => offset_s.clone(),
        "Epoch" => epoch_str.clone(),
        "RIC X (km)" => ric_x_km,
        "RIC Y (km)" => ric_y_km,
        "RIC Z (km)" => ric_z_km,
        "RIC VX (km/s)" => ric_vx_km_s,
        "RIC VY (km/s)" => ric_vy_km_s,
        "RIC VZ (km/s)" => ric_vz_km_s,
    )?;

    println!("RIC difference at start\n{}", ric_df.head(Some(10)));
    println!("RIC difference at end\n{}", ric_df.tail(Some(10)));

    let aer_df = df!(
        "Offset (s)" => offset_s.clone(),
        "Epoch" => epoch_str.clone(),
        "azimuth (deg)" => azimuth_deg,
        "elevation (deg)" => elevation_deg,
        "range (km)" => range_km,
        "range rate (km/s)" => range_rate_km_s,
    )?;

    // Finally, let's see when the spacecraft is visible, assuming 15 degrees minimum elevation.
    let mask = aer_df.column("elevation (deg)")?.gt(15.0)?;
    let cubesat_visible = aer_df.filter(&mask)?;

    println!("{cubesat_visible}");

    Ok(())
}

impl<S: Interpolatable> Traj<S>

where DefaultAllocator: Allocator<S::VecLength> + Allocator<S::Size> + Allocator<S::Size, S::Size>,

pub fn new() -> Self

pub fn finalize(&mut self)

Orders the states, can be used to store the states out of order

pub fn at(&self, epoch: Epoch) -> Result<S, TrajError>

Evaluate the trajectory at this specific epoch.

Examples found in repository

examples/04_lro_od/main.rs (line 271)

fn main() -> Result<(), Box<dyn Error>> {
    pel::init();

    // ====================== //
    // === ALMANAC SET UP === //
    // ====================== //

    // Dynamics models require planetary constants and ephemerides to be defined.
    // Let's start by grabbing those by using ANISE's MetaAlmanac.

    let data_folder: PathBuf = [env!("CARGO_MANIFEST_DIR"), "examples", "04_lro_od"]
        .iter()
        .collect();

    let meta = data_folder.join("lro-dynamics.dhall");

    // Load this ephem in the general Almanac we're using for this analysis.
    let mut almanac = MetaAlmanac::new(meta.to_string_lossy().to_string())
        .map_err(Box::new)?
        .process(true)
        .map_err(Box::new)?;

    let mut moon_pc = almanac.planetary_data.get_by_id(MOON)?;
    moon_pc.mu_km3_s2 = 4902.74987;
    almanac.planetary_data.set_by_id(MOON, moon_pc)?;

    let mut earth_pc = almanac.planetary_data.get_by_id(EARTH)?;
    earth_pc.mu_km3_s2 = 398600.436;
    almanac.planetary_data.set_by_id(EARTH, earth_pc)?;

    // Save this new kernel for reuse.
    // In an operational context, this would be part of the "Lock" process, and should not change throughout the mission.
    almanac
        .planetary_data
        .save_as(&data_folder.join("lro-specific.pca"), true)?;

    // Lock the almanac (an Arc is a read only structure).
    let almanac = Arc::new(almanac);

    // Orbit determination requires a Trajectory structure, which can be saved as parquet file.
    // In our case, the trajectory comes from the BSP file, so we need to build a Trajectory from the almanac directly.
    // To query the Almanac, we need to build the LRO frame in the J2000 orientation in our case.
    // Inspecting the LRO BSP in the ANISE GUI shows us that NASA has assigned ID -85 to LRO.
    let lro_frame = Frame::from_ephem_j2000(-85);

    // To build the trajectory we need to provide a spacecraft template.
    let sc_template = Spacecraft::builder()
        .dry_mass_kg(1018.0) // Launch masses
        .fuel_mass_kg(900.0)
        .srp(SrpConfig {
            // SRP configuration is arbitrary, but we will be estimating it anyway.
            area_m2: 3.9 * 2.7,
            cr: 0.96,
        })
        .orbit(Orbit::zero(MOON_J2000)) // Setting a zero orbit here because it's just a template
        .build();
    // Now we can build the trajectory from the BSP file.
    // We'll arbitrarily set the tracking arc to 48 hours with a one minute time step.
    let traj_as_flown = Traj::from_bsp(
        lro_frame,
        MOON_J2000,
        almanac.clone(),
        sc_template,
        5.seconds(),
        Some(Epoch::from_str("2024-01-01 00:00:00 UTC")?),
        Some(Epoch::from_str("2024-01-02 00:00:00 UTC")?),
        Aberration::LT,
        Some("LRO".to_string()),
    )?;

    println!("{traj_as_flown}");

    // ====================== //
    // === MODEL MATCHING === //
    // ====================== //

    // Set up the spacecraft dynamics.

    // Specify that the orbital dynamics must account for the graviational pull of the Earth and the Sun.
    // The gravity of the Moon will also be accounted for since the spaceraft in a lunar orbit.
    let mut orbital_dyn = OrbitalDynamics::point_masses(vec![EARTH, SUN, JUPITER_BARYCENTER]);

    // We want to include the spherical harmonics, so let's download the gravitational data from the Nyx Cloud.
    // We're using the GRAIL JGGRX model.
    let mut jggrx_meta = MetaFile {
        uri: "http://public-data.nyxspace.com/nyx/models/Luna_jggrx_1500e_sha.tab.gz".to_string(),
        crc32: Some(0x6bcacda8), // Specifying the CRC32 avoids redownloading it if it's cached.
    };
    // And let's download it if we don't have it yet.
    jggrx_meta.process(true)?;

    // Build the spherical harmonics.
    // The harmonics must be computed in the body fixed frame.
    // We're using the long term prediction of the Moon principal axes frame.
    let moon_pa_frame = MOON_PA_FRAME.with_orient(31008);
    // let moon_pa_frame = IAU_MOON_FRAME;
    let sph_harmonics = Harmonics::from_stor(
        almanac.frame_from_uid(moon_pa_frame)?,
        HarmonicsMem::from_shadr(&jggrx_meta.uri, 80, 80, true)?,
    );

    // Include the spherical harmonics into the orbital dynamics.
    orbital_dyn.accel_models.push(sph_harmonics);

    // We define the solar radiation pressure, using the default solar flux and accounting only
    // for the eclipsing caused by the Earth and Moon.
    // Note that by default, enabling the SolarPressure model will also enable the estimation of the coefficient of reflectivity.
    let srp_dyn = SolarPressure::new(vec![EARTH_J2000, MOON_J2000], almanac.clone())?;

    // Finalize setting up the dynamics, specifying the force models (orbital_dyn) separately from the
    // acceleration models (SRP in this case). Use `from_models` to specify multiple accel models.
    let dynamics = SpacecraftDynamics::from_model(orbital_dyn, srp_dyn);

    println!("{dynamics}");

    // Now we can build the propagator.
    let setup = Propagator::default_dp78(dynamics.clone());

    // For reference, let's build the trajectory with Nyx's models from that LRO state.
    let (sim_final, traj_as_sim) = setup
        .with(*traj_as_flown.first(), almanac.clone())
        .until_epoch_with_traj(traj_as_flown.last().epoch())?;

    println!("SIM INIT:  {:x}", traj_as_flown.first());
    println!("SIM FINAL: {sim_final:x}");
    // Compute RIC difference between SIM and LRO ephem
    let sim_lro_delta = sim_final
        .orbit
        .ric_difference(&traj_as_flown.last().orbit)?;
    println!("{traj_as_sim}");
    println!(
        "SIM v LRO - RIC Position (m): {:.3}",
        sim_lro_delta.radius_km * 1e3
    );
    println!(
        "SIM v LRO - RIC Velocity (m/s): {:.3}",
        sim_lro_delta.velocity_km_s * 1e3
    );

    traj_as_sim.ric_diff_to_parquet(
        &traj_as_flown,
        "./04_lro_sim_truth_error.parquet",
        ExportCfg::default(),
    )?;

    // ==================== //
    // === OD SIMULATOR === //
    // ==================== //

    // After quite some time trying to exactly match the model, we still end up with an oscillatory difference on the order of 150 meters between the propagated state
    // and the truth LRO state.

    // Therefore, we will actually run an estimation from a dispersed LRO state.
    // The sc_seed is the true LRO state from the BSP.
    let sc_seed = *traj_as_flown.first();

    // Load the Deep Space Network ground stations.
    // Nyx allows you to build these at runtime but it's pretty static so we can just load them from YAML.
    let ground_station_file: PathBuf = [
        env!("CARGO_MANIFEST_DIR"),
        "examples",
        "04_lro_od",
        "dsn-network.yaml",
    ]
    .iter()
    .collect();

    let devices = GroundStation::load_many(ground_station_file)?;

    // Typical OD software requires that you specify your own tracking schedule or you'll have overlapping measurements.
    // Nyx can build a tracking schedule for you based on the first station with access.
    let trkconfg_yaml: PathBuf = [
        env!("CARGO_MANIFEST_DIR"),
        "examples",
        "04_lro_od",
        "tracking-cfg.yaml",
    ]
    .iter()
    .collect();

    let configs: BTreeMap<String, TrkConfig> = TrkConfig::load_named(trkconfg_yaml)?;

    // Build the tracking arc simulation to generate a "standard measurement".
    let mut trk = TrackingArcSim::<Spacecraft, RangeDoppler, _>::new(
        devices,
        traj_as_flown.clone(),
        configs,
    )?;

    trk.build_schedule(almanac.clone())?;
    let arc = trk.generate_measurements(almanac.clone())?;
    // Save the simulated tracking data
    arc.to_parquet_simple("./04_lro_simulated_tracking.parquet")?;

    // We'll note that in our case, we have continuous coverage of LRO when the vehicle is not behind the Moon.
    println!("{arc}");

    // Now that we have simulated measurements, we'll run the orbit determination.

    // ===================== //
    // === OD ESTIMATION === //
    // ===================== //

    let sc = SpacecraftUncertainty::builder()
        .nominal(sc_seed)
        .frame(LocalFrame::RIC)
        .x_km(0.5)
        .y_km(0.5)
        .z_km(0.5)
        .vx_km_s(5e-3)
        .vy_km_s(5e-3)
        .vz_km_s(5e-3)
        .build();

    // Build the filter initial estimate, which we will reuse in the filter.
    let initial_estimate = sc.to_estimate()?;

    println!("== FILTER STATE ==\n{sc_seed:x}\n{initial_estimate}");

    let kf = KF::new(
        // Increase the initial covariance to account for larger deviation.
        initial_estimate,
        // Until https://github.com/nyx-space/nyx/issues/351, we need to specify the SNC in the acceleration of the Moon J2000 frame.
        SNC3::from_diagonal(10 * Unit::Minute, &[1e-11, 1e-11, 1e-11]),
    );

    // We'll set up the OD process to reject measurements whose residuals are mover than 4 sigmas away from what we expect.
    let mut odp = ODProcess::ckf(
        setup.with(initial_estimate.state().with_stm(), almanac.clone()),
        kf,
        Some(ResidRejectCrit::default()),
        almanac.clone(),
    );

    odp.process_arc::<GroundStation>(&arc)?;

    let ric_err = traj_as_flown
        .at(odp.estimates.last().unwrap().epoch())?
        .orbit
        .ric_difference(&odp.estimates.last().unwrap().orbital_state())?;
    println!("== RIC at end ==");
    println!("RIC Position (m): {}", ric_err.radius_km * 1e3);
    println!("RIC Velocity (m/s): {}", ric_err.velocity_km_s * 1e3);

    odp.to_parquet("./04_lro_od_results.parquet", ExportCfg::default())?;

    // In our case, we have the truth trajectory from NASA.
    // So we can compute the RIC state difference between the real LRO ephem and what we've just estimated.
    // Export the OD trajectory first.
    let od_trajectory = odp.to_traj()?;
    // Build the RIC difference.
    od_trajectory.ric_diff_to_parquet(
        &traj_as_flown,
        "./04_lro_od_truth_error.parquet",
        ExportCfg::default(),
    )?;

    Ok(())
}

pub fn first(&self) -> &S

Returns the first state in this ephemeris

Examples found in repository

examples/04_lro_od/main.rs (line 154)

fn main() -> Result<(), Box<dyn Error>> {
    pel::init();

    // ====================== //
    // === ALMANAC SET UP === //
    // ====================== //

    // Dynamics models require planetary constants and ephemerides to be defined.
    // Let's start by grabbing those by using ANISE's MetaAlmanac.

    let data_folder: PathBuf = [env!("CARGO_MANIFEST_DIR"), "examples", "04_lro_od"]
        .iter()
        .collect();

    let meta = data_folder.join("lro-dynamics.dhall");

    // Load this ephem in the general Almanac we're using for this analysis.
    let mut almanac = MetaAlmanac::new(meta.to_string_lossy().to_string())
        .map_err(Box::new)?
        .process(true)
        .map_err(Box::new)?;

    let mut moon_pc = almanac.planetary_data.get_by_id(MOON)?;
    moon_pc.mu_km3_s2 = 4902.74987;
    almanac.planetary_data.set_by_id(MOON, moon_pc)?;

    let mut earth_pc = almanac.planetary_data.get_by_id(EARTH)?;
    earth_pc.mu_km3_s2 = 398600.436;
    almanac.planetary_data.set_by_id(EARTH, earth_pc)?;

    // Save this new kernel for reuse.
    // In an operational context, this would be part of the "Lock" process, and should not change throughout the mission.
    almanac
        .planetary_data
        .save_as(&data_folder.join("lro-specific.pca"), true)?;

    // Lock the almanac (an Arc is a read only structure).
    let almanac = Arc::new(almanac);

    // Orbit determination requires a Trajectory structure, which can be saved as parquet file.
    // In our case, the trajectory comes from the BSP file, so we need to build a Trajectory from the almanac directly.
    // To query the Almanac, we need to build the LRO frame in the J2000 orientation in our case.
    // Inspecting the LRO BSP in the ANISE GUI shows us that NASA has assigned ID -85 to LRO.
    let lro_frame = Frame::from_ephem_j2000(-85);

    // To build the trajectory we need to provide a spacecraft template.
    let sc_template = Spacecraft::builder()
        .dry_mass_kg(1018.0) // Launch masses
        .fuel_mass_kg(900.0)
        .srp(SrpConfig {
            // SRP configuration is arbitrary, but we will be estimating it anyway.
            area_m2: 3.9 * 2.7,
            cr: 0.96,
        })
        .orbit(Orbit::zero(MOON_J2000)) // Setting a zero orbit here because it's just a template
        .build();
    // Now we can build the trajectory from the BSP file.
    // We'll arbitrarily set the tracking arc to 48 hours with a one minute time step.
    let traj_as_flown = Traj::from_bsp(
        lro_frame,
        MOON_J2000,
        almanac.clone(),
        sc_template,
        5.seconds(),
        Some(Epoch::from_str("2024-01-01 00:00:00 UTC")?),
        Some(Epoch::from_str("2024-01-02 00:00:00 UTC")?),
        Aberration::LT,
        Some("LRO".to_string()),
    )?;

    println!("{traj_as_flown}");

    // ====================== //
    // === MODEL MATCHING === //
    // ====================== //

    // Set up the spacecraft dynamics.

    // Specify that the orbital dynamics must account for the graviational pull of the Earth and the Sun.
    // The gravity of the Moon will also be accounted for since the spaceraft in a lunar orbit.
    let mut orbital_dyn = OrbitalDynamics::point_masses(vec![EARTH, SUN, JUPITER_BARYCENTER]);

    // We want to include the spherical harmonics, so let's download the gravitational data from the Nyx Cloud.
    // We're using the GRAIL JGGRX model.
    let mut jggrx_meta = MetaFile {
        uri: "http://public-data.nyxspace.com/nyx/models/Luna_jggrx_1500e_sha.tab.gz".to_string(),
        crc32: Some(0x6bcacda8), // Specifying the CRC32 avoids redownloading it if it's cached.
    };
    // And let's download it if we don't have it yet.
    jggrx_meta.process(true)?;

    // Build the spherical harmonics.
    // The harmonics must be computed in the body fixed frame.
    // We're using the long term prediction of the Moon principal axes frame.
    let moon_pa_frame = MOON_PA_FRAME.with_orient(31008);
    // let moon_pa_frame = IAU_MOON_FRAME;
    let sph_harmonics = Harmonics::from_stor(
        almanac.frame_from_uid(moon_pa_frame)?,
        HarmonicsMem::from_shadr(&jggrx_meta.uri, 80, 80, true)?,
    );

    // Include the spherical harmonics into the orbital dynamics.
    orbital_dyn.accel_models.push(sph_harmonics);

    // We define the solar radiation pressure, using the default solar flux and accounting only
    // for the eclipsing caused by the Earth and Moon.
    // Note that by default, enabling the SolarPressure model will also enable the estimation of the coefficient of reflectivity.
    let srp_dyn = SolarPressure::new(vec![EARTH_J2000, MOON_J2000], almanac.clone())?;

    // Finalize setting up the dynamics, specifying the force models (orbital_dyn) separately from the
    // acceleration models (SRP in this case). Use `from_models` to specify multiple accel models.
    let dynamics = SpacecraftDynamics::from_model(orbital_dyn, srp_dyn);

    println!("{dynamics}");

    // Now we can build the propagator.
    let setup = Propagator::default_dp78(dynamics.clone());

    // For reference, let's build the trajectory with Nyx's models from that LRO state.
    let (sim_final, traj_as_sim) = setup
        .with(*traj_as_flown.first(), almanac.clone())
        .until_epoch_with_traj(traj_as_flown.last().epoch())?;

    println!("SIM INIT:  {:x}", traj_as_flown.first());
    println!("SIM FINAL: {sim_final:x}");
    // Compute RIC difference between SIM and LRO ephem
    let sim_lro_delta = sim_final
        .orbit
        .ric_difference(&traj_as_flown.last().orbit)?;
    println!("{traj_as_sim}");
    println!(
        "SIM v LRO - RIC Position (m): {:.3}",
        sim_lro_delta.radius_km * 1e3
    );
    println!(
        "SIM v LRO - RIC Velocity (m/s): {:.3}",
        sim_lro_delta.velocity_km_s * 1e3
    );

    traj_as_sim.ric_diff_to_parquet(
        &traj_as_flown,
        "./04_lro_sim_truth_error.parquet",
        ExportCfg::default(),
    )?;

    // ==================== //
    // === OD SIMULATOR === //
    // ==================== //

    // After quite some time trying to exactly match the model, we still end up with an oscillatory difference on the order of 150 meters between the propagated state
    // and the truth LRO state.

    // Therefore, we will actually run an estimation from a dispersed LRO state.
    // The sc_seed is the true LRO state from the BSP.
    let sc_seed = *traj_as_flown.first();

    // Load the Deep Space Network ground stations.
    // Nyx allows you to build these at runtime but it's pretty static so we can just load them from YAML.
    let ground_station_file: PathBuf = [
        env!("CARGO_MANIFEST_DIR"),
        "examples",
        "04_lro_od",
        "dsn-network.yaml",
    ]
    .iter()
    .collect();

    let devices = GroundStation::load_many(ground_station_file)?;

    // Typical OD software requires that you specify your own tracking schedule or you'll have overlapping measurements.
    // Nyx can build a tracking schedule for you based on the first station with access.
    let trkconfg_yaml: PathBuf = [
        env!("CARGO_MANIFEST_DIR"),
        "examples",
        "04_lro_od",
        "tracking-cfg.yaml",
    ]
    .iter()
    .collect();

    let configs: BTreeMap<String, TrkConfig> = TrkConfig::load_named(trkconfg_yaml)?;

    // Build the tracking arc simulation to generate a "standard measurement".
    let mut trk = TrackingArcSim::<Spacecraft, RangeDoppler, _>::new(
        devices,
        traj_as_flown.clone(),
        configs,
    )?;

    trk.build_schedule(almanac.clone())?;
    let arc = trk.generate_measurements(almanac.clone())?;
    // Save the simulated tracking data
    arc.to_parquet_simple("./04_lro_simulated_tracking.parquet")?;

    // We'll note that in our case, we have continuous coverage of LRO when the vehicle is not behind the Moon.
    println!("{arc}");

    // Now that we have simulated measurements, we'll run the orbit determination.

    // ===================== //
    // === OD ESTIMATION === //
    // ===================== //

    let sc = SpacecraftUncertainty::builder()
        .nominal(sc_seed)
        .frame(LocalFrame::RIC)
        .x_km(0.5)
        .y_km(0.5)
        .z_km(0.5)
        .vx_km_s(5e-3)
        .vy_km_s(5e-3)
        .vz_km_s(5e-3)
        .build();

    // Build the filter initial estimate, which we will reuse in the filter.
    let initial_estimate = sc.to_estimate()?;

    println!("== FILTER STATE ==\n{sc_seed:x}\n{initial_estimate}");

    let kf = KF::new(
        // Increase the initial covariance to account for larger deviation.
        initial_estimate,
        // Until https://github.com/nyx-space/nyx/issues/351, we need to specify the SNC in the acceleration of the Moon J2000 frame.
        SNC3::from_diagonal(10 * Unit::Minute, &[1e-11, 1e-11, 1e-11]),
    );

    // We'll set up the OD process to reject measurements whose residuals are mover than 4 sigmas away from what we expect.
    let mut odp = ODProcess::ckf(
        setup.with(initial_estimate.state().with_stm(), almanac.clone()),
        kf,
        Some(ResidRejectCrit::default()),
        almanac.clone(),
    );

    odp.process_arc::<GroundStation>(&arc)?;

    let ric_err = traj_as_flown
        .at(odp.estimates.last().unwrap().epoch())?
        .orbit
        .ric_difference(&odp.estimates.last().unwrap().orbital_state())?;
    println!("== RIC at end ==");
    println!("RIC Position (m): {}", ric_err.radius_km * 1e3);
    println!("RIC Velocity (m/s): {}", ric_err.velocity_km_s * 1e3);

    odp.to_parquet("./04_lro_od_results.parquet", ExportCfg::default())?;

    // In our case, we have the truth trajectory from NASA.
    // So we can compute the RIC state difference between the real LRO ephem and what we've just estimated.
    // Export the OD trajectory first.
    let od_trajectory = odp.to_traj()?;
    // Build the RIC difference.
    od_trajectory.ric_diff_to_parquet(
        &traj_as_flown,
        "./04_lro_od_truth_error.parquet",
        ExportCfg::default(),
    )?;

    Ok(())
}

pub fn last(&self) -> &S

Returns the last state in this ephemeris

Examples found in repository

examples/04_lro_od/main.rs (line 155)

fn main() -> Result<(), Box<dyn Error>> {
    pel::init();

    // ====================== //
    // === ALMANAC SET UP === //
    // ====================== //

    // Dynamics models require planetary constants and ephemerides to be defined.
    // Let's start by grabbing those by using ANISE's MetaAlmanac.

    let data_folder: PathBuf = [env!("CARGO_MANIFEST_DIR"), "examples", "04_lro_od"]
        .iter()
        .collect();

    let meta = data_folder.join("lro-dynamics.dhall");

    // Load this ephem in the general Almanac we're using for this analysis.
    let mut almanac = MetaAlmanac::new(meta.to_string_lossy().to_string())
        .map_err(Box::new)?
        .process(true)
        .map_err(Box::new)?;

    let mut moon_pc = almanac.planetary_data.get_by_id(MOON)?;
    moon_pc.mu_km3_s2 = 4902.74987;
    almanac.planetary_data.set_by_id(MOON, moon_pc)?;

    let mut earth_pc = almanac.planetary_data.get_by_id(EARTH)?;
    earth_pc.mu_km3_s2 = 398600.436;
    almanac.planetary_data.set_by_id(EARTH, earth_pc)?;

    // Save this new kernel for reuse.
    // In an operational context, this would be part of the "Lock" process, and should not change throughout the mission.
    almanac
        .planetary_data
        .save_as(&data_folder.join("lro-specific.pca"), true)?;

    // Lock the almanac (an Arc is a read only structure).
    let almanac = Arc::new(almanac);

    // Orbit determination requires a Trajectory structure, which can be saved as parquet file.
    // In our case, the trajectory comes from the BSP file, so we need to build a Trajectory from the almanac directly.
    // To query the Almanac, we need to build the LRO frame in the J2000 orientation in our case.
    // Inspecting the LRO BSP in the ANISE GUI shows us that NASA has assigned ID -85 to LRO.
    let lro_frame = Frame::from_ephem_j2000(-85);

    // To build the trajectory we need to provide a spacecraft template.
    let sc_template = Spacecraft::builder()
        .dry_mass_kg(1018.0) // Launch masses
        .fuel_mass_kg(900.0)
        .srp(SrpConfig {
            // SRP configuration is arbitrary, but we will be estimating it anyway.
            area_m2: 3.9 * 2.7,
            cr: 0.96,
        })
        .orbit(Orbit::zero(MOON_J2000)) // Setting a zero orbit here because it's just a template
        .build();
    // Now we can build the trajectory from the BSP file.
    // We'll arbitrarily set the tracking arc to 48 hours with a one minute time step.
    let traj_as_flown = Traj::from_bsp(
        lro_frame,
        MOON_J2000,
        almanac.clone(),
        sc_template,
        5.seconds(),
        Some(Epoch::from_str("2024-01-01 00:00:00 UTC")?),
        Some(Epoch::from_str("2024-01-02 00:00:00 UTC")?),
        Aberration::LT,
        Some("LRO".to_string()),
    )?;

    println!("{traj_as_flown}");

    // ====================== //
    // === MODEL MATCHING === //
    // ====================== //

    // Set up the spacecraft dynamics.

    // Specify that the orbital dynamics must account for the graviational pull of the Earth and the Sun.
    // The gravity of the Moon will also be accounted for since the spaceraft in a lunar orbit.
    let mut orbital_dyn = OrbitalDynamics::point_masses(vec![EARTH, SUN, JUPITER_BARYCENTER]);

    // We want to include the spherical harmonics, so let's download the gravitational data from the Nyx Cloud.
    // We're using the GRAIL JGGRX model.
    let mut jggrx_meta = MetaFile {
        uri: "http://public-data.nyxspace.com/nyx/models/Luna_jggrx_1500e_sha.tab.gz".to_string(),
        crc32: Some(0x6bcacda8), // Specifying the CRC32 avoids redownloading it if it's cached.
    };
    // And let's download it if we don't have it yet.
    jggrx_meta.process(true)?;

    // Build the spherical harmonics.
    // The harmonics must be computed in the body fixed frame.
    // We're using the long term prediction of the Moon principal axes frame.
    let moon_pa_frame = MOON_PA_FRAME.with_orient(31008);
    // let moon_pa_frame = IAU_MOON_FRAME;
    let sph_harmonics = Harmonics::from_stor(
        almanac.frame_from_uid(moon_pa_frame)?,
        HarmonicsMem::from_shadr(&jggrx_meta.uri, 80, 80, true)?,
    );

    // Include the spherical harmonics into the orbital dynamics.
    orbital_dyn.accel_models.push(sph_harmonics);

    // We define the solar radiation pressure, using the default solar flux and accounting only
    // for the eclipsing caused by the Earth and Moon.
    // Note that by default, enabling the SolarPressure model will also enable the estimation of the coefficient of reflectivity.
    let srp_dyn = SolarPressure::new(vec![EARTH_J2000, MOON_J2000], almanac.clone())?;

    // Finalize setting up the dynamics, specifying the force models (orbital_dyn) separately from the
    // acceleration models (SRP in this case). Use `from_models` to specify multiple accel models.
    let dynamics = SpacecraftDynamics::from_model(orbital_dyn, srp_dyn);

    println!("{dynamics}");

    // Now we can build the propagator.
    let setup = Propagator::default_dp78(dynamics.clone());

    // For reference, let's build the trajectory with Nyx's models from that LRO state.
    let (sim_final, traj_as_sim) = setup
        .with(*traj_as_flown.first(), almanac.clone())
        .until_epoch_with_traj(traj_as_flown.last().epoch())?;

    println!("SIM INIT:  {:x}", traj_as_flown.first());
    println!("SIM FINAL: {sim_final:x}");
    // Compute RIC difference between SIM and LRO ephem
    let sim_lro_delta = sim_final
        .orbit
        .ric_difference(&traj_as_flown.last().orbit)?;
    println!("{traj_as_sim}");
    println!(
        "SIM v LRO - RIC Position (m): {:.3}",
        sim_lro_delta.radius_km * 1e3
    );
    println!(
        "SIM v LRO - RIC Velocity (m/s): {:.3}",
        sim_lro_delta.velocity_km_s * 1e3
    );

    traj_as_sim.ric_diff_to_parquet(
        &traj_as_flown,
        "./04_lro_sim_truth_error.parquet",
        ExportCfg::default(),
    )?;

    // ==================== //
    // === OD SIMULATOR === //
    // ==================== //

    // After quite some time trying to exactly match the model, we still end up with an oscillatory difference on the order of 150 meters between the propagated state
    // and the truth LRO state.

    // Therefore, we will actually run an estimation from a dispersed LRO state.
    // The sc_seed is the true LRO state from the BSP.
    let sc_seed = *traj_as_flown.first();

    // Load the Deep Space Network ground stations.
    // Nyx allows you to build these at runtime but it's pretty static so we can just load them from YAML.
    let ground_station_file: PathBuf = [
        env!("CARGO_MANIFEST_DIR"),
        "examples",
        "04_lro_od",
        "dsn-network.yaml",
    ]
    .iter()
    .collect();

    let devices = GroundStation::load_many(ground_station_file)?;

    // Typical OD software requires that you specify your own tracking schedule or you'll have overlapping measurements.
    // Nyx can build a tracking schedule for you based on the first station with access.
    let trkconfg_yaml: PathBuf = [
        env!("CARGO_MANIFEST_DIR"),
        "examples",
        "04_lro_od",
        "tracking-cfg.yaml",
    ]
    .iter()
    .collect();

    let configs: BTreeMap<String, TrkConfig> = TrkConfig::load_named(trkconfg_yaml)?;

    // Build the tracking arc simulation to generate a "standard measurement".
    let mut trk = TrackingArcSim::<Spacecraft, RangeDoppler, _>::new(
        devices,
        traj_as_flown.clone(),
        configs,
    )?;

    trk.build_schedule(almanac.clone())?;
    let arc = trk.generate_measurements(almanac.clone())?;
    // Save the simulated tracking data
    arc.to_parquet_simple("./04_lro_simulated_tracking.parquet")?;

    // We'll note that in our case, we have continuous coverage of LRO when the vehicle is not behind the Moon.
    println!("{arc}");

    // Now that we have simulated measurements, we'll run the orbit determination.

    // ===================== //
    // === OD ESTIMATION === //
    // ===================== //

    let sc = SpacecraftUncertainty::builder()
        .nominal(sc_seed)
        .frame(LocalFrame::RIC)
        .x_km(0.5)
        .y_km(0.5)
        .z_km(0.5)
        .vx_km_s(5e-3)
        .vy_km_s(5e-3)
        .vz_km_s(5e-3)
        .build();

    // Build the filter initial estimate, which we will reuse in the filter.
    let initial_estimate = sc.to_estimate()?;

    println!("== FILTER STATE ==\n{sc_seed:x}\n{initial_estimate}");

    let kf = KF::new(
        // Increase the initial covariance to account for larger deviation.
        initial_estimate,
        // Until https://github.com/nyx-space/nyx/issues/351, we need to specify the SNC in the acceleration of the Moon J2000 frame.
        SNC3::from_diagonal(10 * Unit::Minute, &[1e-11, 1e-11, 1e-11]),
    );

    // We'll set up the OD process to reject measurements whose residuals are mover than 4 sigmas away from what we expect.
    let mut odp = ODProcess::ckf(
        setup.with(initial_estimate.state().with_stm(), almanac.clone()),
        kf,
        Some(ResidRejectCrit::default()),
        almanac.clone(),
    );

    odp.process_arc::<GroundStation>(&arc)?;

    let ric_err = traj_as_flown
        .at(odp.estimates.last().unwrap().epoch())?
        .orbit
        .ric_difference(&odp.estimates.last().unwrap().orbital_state())?;
    println!("== RIC at end ==");
    println!("RIC Position (m): {}", ric_err.radius_km * 1e3);
    println!("RIC Velocity (m/s): {}", ric_err.velocity_km_s * 1e3);

    odp.to_parquet("./04_lro_od_results.parquet", ExportCfg::default())?;

    // In our case, we have the truth trajectory from NASA.
    // So we can compute the RIC state difference between the real LRO ephem and what we've just estimated.
    // Export the OD trajectory first.
    let od_trajectory = odp.to_traj()?;
    // Build the RIC difference.
    od_trajectory.ric_diff_to_parquet(
        &traj_as_flown,
        "./04_lro_od_truth_error.parquet",
        ExportCfg::default(),
    )?;

    Ok(())
}

pub fn every(&self, step: Duration) -> TrajIterator<'_, S>

Creates an iterator through the trajectory by the provided step size

Examples found in repository

examples/03_geo_analysis/drift.rs (line 170)

fn main() -> Result<(), Box<dyn Error>> {
    pel::init();
    // Dynamics models require planetary constants and ephemerides to be defined.
    // Let's start by grabbing those by using ANISE's latest MetaAlmanac.
    // This will automatically download the DE440s planetary ephemeris,
    // the daily-updated Earth Orientation Parameters, the high fidelity Moon orientation
    // parameters (for the Moon Mean Earth and Moon Principal Axes frames), and the PCK11
    // planetary constants kernels.
    // For details, refer to https://github.com/nyx-space/anise/blob/master/data/latest.dhall.
    // Note that we place the Almanac into an Arc so we can clone it cheaply and provide read-only
    // references to many functions.
    let almanac = Arc::new(MetaAlmanac::latest().map_err(Box::new)?);
    // Define the orbit epoch
    let epoch = Epoch::from_gregorian_utc_hms(2024, 2, 29, 12, 13, 14);

    // Define the orbit.
    // First we need to fetch the Earth J2000 from information from the Almanac.
    // This allows the frame to include the gravitational parameters and the shape of the Earth,
    // defined as a tri-axial ellipoid. Note that this shape can be changed manually or in the Almanac
    // by loading a different set of planetary constants.
    let earth_j2000 = almanac.frame_from_uid(EARTH_J2000)?;

    // Placing this GEO bird just above Colorado.
    // In theory, the eccentricity is zero, but in practice, it's about 1e-5 to 1e-6 at best.
    let orbit = Orbit::try_keplerian(42164.0, 1e-5, 0., 163.0, 75.0, 0.0, epoch, earth_j2000)?;
    // Print in in Keplerian form.
    println!("{orbit:x}");

    let state_bf = almanac.transform_to(orbit, IAU_EARTH_FRAME, None)?;
    let (orig_lat_deg, orig_long_deg, orig_alt_km) = state_bf.latlongalt()?;

    // Nyx is used for high fidelity propagation, not Keplerian propagation as above.
    // Nyx only propagates Spacecraft at the moment, which allows it to account for acceleration
    // models such as solar radiation pressure.

    // Let's build a cubesat sized spacecraft, with an SRP area of 10 cm^2 and a mass of 9.6 kg.
    let sc = Spacecraft::builder()
        .orbit(orbit)
        .dry_mass_kg(9.60)
        .srp(SrpConfig {
            area_m2: 10e-4,
            cr: 1.1,
        })
        .build();
    println!("{sc:x}");

    // Set up the spacecraft dynamics.

    // Specify that the orbital dynamics must account for the graviational pull of the Moon and the Sun.
    // The gravity of the Earth will also be accounted for since the spaceraft in an Earth orbit.
    let mut orbital_dyn = OrbitalDynamics::point_masses(vec![MOON, SUN]);

    // We want to include the spherical harmonics, so let's download the gravitational data from the Nyx Cloud.
    // We're using the JGM3 model here, which is the default in GMAT.
    let mut jgm3_meta = MetaFile {
        uri: "http://public-data.nyxspace.com/nyx/models/JGM3.cof.gz".to_string(),
        crc32: Some(0xF446F027), // Specifying the CRC32 avoids redownloading it if it's cached.
    };
    // And let's download it if we don't have it yet.
    jgm3_meta.process(true)?;

    // Build the spherical harmonics.
    // The harmonics must be computed in the body fixed frame.
    // We're using the long term prediction of the Earth centered Earth fixed frame, IAU Earth.
    let harmonics_21x21 = Harmonics::from_stor(
        almanac.frame_from_uid(IAU_EARTH_FRAME)?,
        HarmonicsMem::from_cof(&jgm3_meta.uri, 21, 21, true).unwrap(),
    );

    // Include the spherical harmonics into the orbital dynamics.
    orbital_dyn.accel_models.push(harmonics_21x21);

    // We define the solar radiation pressure, using the default solar flux and accounting only
    // for the eclipsing caused by the Earth and Moon.
    let srp_dyn = SolarPressure::new(vec![EARTH_J2000, MOON_J2000], almanac.clone())?;

    // Finalize setting up the dynamics, specifying the force models (orbital_dyn) separately from the
    // acceleration models (SRP in this case). Use `from_models` to specify multiple accel models.
    let dynamics = SpacecraftDynamics::from_model(orbital_dyn, srp_dyn);

    println!("{dynamics}");

    // Finally, let's propagate this orbit to the same epoch as above.
    // The first returned value is the spacecraft state at the final epoch.
    // The second value is the full trajectory where the step size is variable step used by the propagator.
    let (future_sc, trajectory) = Propagator::default(dynamics)
        .with(sc, almanac.clone())
        .until_epoch_with_traj(epoch + Unit::Century * 0.03)?;

    println!("=== High fidelity propagation ===");
    println!(
        "SMA changed by {:.3} km",
        orbit.sma_km()? - future_sc.orbit.sma_km()?
    );
    println!(
        "ECC changed by {:.6}",
        orbit.ecc()? - future_sc.orbit.ecc()?
    );
    println!(
        "INC changed by {:.3e} deg",
        orbit.inc_deg()? - future_sc.orbit.inc_deg()?
    );
    println!(
        "RAAN changed by {:.3} deg",
        orbit.raan_deg()? - future_sc.orbit.raan_deg()?
    );
    println!(
        "AOP changed by {:.3} deg",
        orbit.aop_deg()? - future_sc.orbit.aop_deg()?
    );
    println!(
        "TA changed by {:.3} deg",
        orbit.ta_deg()? - future_sc.orbit.ta_deg()?
    );

    // We also have access to the full trajectory throughout the propagation.
    println!("{trajectory}");

    println!("Spacecraft params after 3 years without active control:\n{future_sc:x}");

    // With the trajectory, let's build a few data products.

    // 1. Export the trajectory as a parquet file, which includes the Keplerian orbital elements.

    let analysis_step = Unit::Minute * 5;

    trajectory.to_parquet(
        "./03_geo_hf_prop.parquet",
        Some(vec![
            &EclipseLocator::cislunar(almanac.clone()).to_penumbra_event()
        ]),
        ExportCfg::builder().step(analysis_step).build(),
        almanac.clone(),
    )?;

    // 2. Compute the latitude, longitude, and altitude throughout the trajectory by rotating the spacecraft position into the Earth body fixed frame.

    // We iterate over the trajectory, grabbing a state every two minutes.
    let mut offset_s = vec![];
    let mut epoch_str = vec![];
    let mut longitude_deg = vec![];
    let mut latitude_deg = vec![];
    let mut altitude_km = vec![];

    for state in trajectory.every(analysis_step) {
        // Convert the GEO bird state into the body fixed frame, and keep track of its latitude, longitude, and altitude.
        // These define the GEO stationkeeping box.

        let this_epoch = state.epoch();

        offset_s.push((this_epoch - orbit.epoch).to_seconds());
        epoch_str.push(this_epoch.to_isoformat());

        let state_bf = almanac.transform_to(state.orbit, IAU_EARTH_FRAME, None)?;
        let (lat_deg, long_deg, alt_km) = state_bf.latlongalt()?;
        longitude_deg.push(long_deg);
        latitude_deg.push(lat_deg);
        altitude_km.push(alt_km);
    }

    println!(
        "Longitude changed by {:.3} deg -- Box is 0.1 deg E-W",
        orig_long_deg - longitude_deg.last().unwrap()
    );

    println!(
        "Latitude changed by {:.3} deg -- Box is 0.05 deg N-S",
        orig_lat_deg - latitude_deg.last().unwrap()
    );

    println!(
        "Altitude changed by {:.3} km -- Box is 30 km",
        orig_alt_km - altitude_km.last().unwrap()
    );

    // Build the station keeping data frame.
    let mut sk_df = df!(
        "Offset (s)" => offset_s.clone(),
        "Epoch (UTC)" => epoch_str.clone(),
        "Longitude E-W (deg)" => longitude_deg,
        "Latitude N-S (deg)" => latitude_deg,
        "Altitude (km)" => altitude_km,

    )?;

    // Create a file to write the Parquet to
    let file = File::create("./03_geo_lla.parquet").expect("Could not create file");

    // Create a ParquetWriter and write the DataFrame to the file
    ParquetWriter::new(file).finish(&mut sk_df)?;

    Ok(())
}

examples/01_orbit_prop/main.rs (line 216)

fn main() -> Result<(), Box<dyn Error>> {
    pel::init();
    // Dynamics models require planetary constants and ephemerides to be defined.
    // Let's start by grabbing those by using ANISE's latest MetaAlmanac.
    // This will automatically download the DE440s planetary ephemeris,
    // the daily-updated Earth Orientation Parameters, the high fidelity Moon orientation
    // parameters (for the Moon Mean Earth and Moon Principal Axes frames), and the PCK11
    // planetary constants kernels.
    // For details, refer to https://github.com/nyx-space/anise/blob/master/data/latest.dhall.
    // Note that we place the Almanac into an Arc so we can clone it cheaply and provide read-only
    // references to many functions.
    let almanac = Arc::new(MetaAlmanac::latest().map_err(Box::new)?);
    // Define the orbit epoch
    let epoch = Epoch::from_gregorian_utc_hms(2024, 2, 29, 12, 13, 14);

    // Define the orbit.
    // First we need to fetch the Earth J2000 from information from the Almanac.
    // This allows the frame to include the gravitational parameters and the shape of the Earth,
    // defined as a tri-axial ellipoid. Note that this shape can be changed manually or in the Almanac
    // by loading a different set of planetary constants.
    let earth_j2000 = almanac.frame_from_uid(EARTH_J2000)?;

    let orbit =
        Orbit::try_keplerian_altitude(300.0, 0.015, 68.5, 65.2, 75.0, 0.0, epoch, earth_j2000)?;
    // Print in in Keplerian form.
    println!("{orbit:x}");

    // There are two ways to propagate an orbit. We can make a quick approximation assuming only two-body
    // motion. This is a useful first order approximation but it isn't used in real-world applications.

    // This approach is a feature of ANISE.
    let future_orbit_tb = orbit.at_epoch(epoch + Unit::Day * 3)?;
    println!("{future_orbit_tb:x}");

    // Two body propagation relies solely on Kepler's laws, so only the true anomaly will change.
    println!(
        "SMA changed by {:.3e} km",
        orbit.sma_km()? - future_orbit_tb.sma_km()?
    );
    println!(
        "ECC changed by {:.3e}",
        orbit.ecc()? - future_orbit_tb.ecc()?
    );
    println!(
        "INC changed by {:.3e} deg",
        orbit.inc_deg()? - future_orbit_tb.inc_deg()?
    );
    println!(
        "RAAN changed by {:.3e} deg",
        orbit.raan_deg()? - future_orbit_tb.raan_deg()?
    );
    println!(
        "AOP changed by {:.3e} deg",
        orbit.aop_deg()? - future_orbit_tb.aop_deg()?
    );
    println!(
        "TA changed by {:.3} deg",
        orbit.ta_deg()? - future_orbit_tb.ta_deg()?
    );

    // Nyx is used for high fidelity propagation, not Keplerian propagation as above.
    // Nyx only propagates Spacecraft at the moment, which allows it to account for acceleration
    // models such as solar radiation pressure.

    // Let's build a cubesat sized spacecraft, with an SRP area of 10 cm^2 and a mass of 9.6 kg.
    let sc = Spacecraft::builder()
        .orbit(orbit)
        .dry_mass_kg(9.60)
        .srp(SrpConfig {
            area_m2: 10e-4,
            cr: 1.1,
        })
        .build();
    println!("{sc:x}");

    // Set up the spacecraft dynamics.

    // Specify that the orbital dynamics must account for the graviational pull of the Moon and the Sun.
    // The gravity of the Earth will also be accounted for since the spaceraft in an Earth orbit.
    let mut orbital_dyn = OrbitalDynamics::point_masses(vec![MOON, SUN]);

    // We want to include the spherical harmonics, so let's download the gravitational data from the Nyx Cloud.
    // We're using the JGM3 model here, which is the default in GMAT.
    let mut jgm3_meta = MetaFile {
        uri: "http://public-data.nyxspace.com/nyx/models/JGM3.cof.gz".to_string(),
        crc32: Some(0xF446F027), // Specifying the CRC32 avoids redownloading it if it's cached.
    };
    // And let's download it if we don't have it yet.
    jgm3_meta.process(true)?;

    // Build the spherical harmonics.
    // The harmonics must be computed in the body fixed frame.
    // We're using the long term prediction of the Earth centered Earth fixed frame, IAU Earth.
    let harmonics_21x21 = Harmonics::from_stor(
        almanac.frame_from_uid(IAU_EARTH_FRAME)?,
        HarmonicsMem::from_cof(&jgm3_meta.uri, 21, 21, true).unwrap(),
    );

    // Include the spherical harmonics into the orbital dynamics.
    orbital_dyn.accel_models.push(harmonics_21x21);

    // We define the solar radiation pressure, using the default solar flux and accounting only
    // for the eclipsing caused by the Earth.
    let srp_dyn = SolarPressure::default(EARTH_J2000, almanac.clone())?;

    // Finalize setting up the dynamics, specifying the force models (orbital_dyn) separately from the
    // acceleration models (SRP in this case). Use `from_models` to specify multiple accel models.
    let dynamics = SpacecraftDynamics::from_model(orbital_dyn, srp_dyn);

    println!("{dynamics}");

    // Finally, let's propagate this orbit to the same epoch as above.
    // The first returned value is the spacecraft state at the final epoch.
    // The second value is the full trajectory where the step size is variable step used by the propagator.
    let (future_sc, trajectory) = Propagator::default(dynamics)
        .with(sc, almanac.clone())
        .until_epoch_with_traj(future_orbit_tb.epoch)?;

    println!("=== High fidelity propagation ===");
    println!(
        "SMA changed by {:.3} km",
        orbit.sma_km()? - future_sc.orbit.sma_km()?
    );
    println!(
        "ECC changed by {:.6}",
        orbit.ecc()? - future_sc.orbit.ecc()?
    );
    println!(
        "INC changed by {:.3e} deg",
        orbit.inc_deg()? - future_sc.orbit.inc_deg()?
    );
    println!(
        "RAAN changed by {:.3} deg",
        orbit.raan_deg()? - future_sc.orbit.raan_deg()?
    );
    println!(
        "AOP changed by {:.3} deg",
        orbit.aop_deg()? - future_sc.orbit.aop_deg()?
    );
    println!(
        "TA changed by {:.3} deg",
        orbit.ta_deg()? - future_sc.orbit.ta_deg()?
    );

    // We also have access to the full trajectory throughout the propagation.
    println!("{trajectory}");

    // With the trajectory, let's build a few data products.

    // 1. Export the trajectory as a CCSDS OEM version 2.0 file and as a parquet file, which includes the Keplerian orbital elements.

    trajectory.to_oem_file(
        "./01_cubesat_hf_prop.oem",
        ExportCfg::builder().step(Unit::Minute * 2).build(),
    )?;

    trajectory.to_parquet_with_cfg(
        "./01_cubesat_hf_prop.parquet",
        ExportCfg::builder().step(Unit::Minute * 2).build(),
        almanac.clone(),
    )?;

    // 2. Compare the difference in the radial-intrack-crosstrack frame between the high fidelity
    // and Keplerian propagation. The RIC frame is commonly used to compute the difference in position
    // and velocity of different spacecraft.
    // 3. Compute the azimuth, elevation, range, and range-rate data of that spacecraft as seen from Boulder, CO, USA.

    let boulder_station = GroundStation::from_point(
        "Boulder, CO, USA".to_string(),
        40.014984,   // latitude in degrees
        -105.270546, // longitude in degrees
        1.6550,      // altitude in kilometers
        almanac.frame_from_uid(IAU_EARTH_FRAME)?,
    );

    // We iterate over the trajectory, grabbing a state every two minutes.
    let mut offset_s = vec![];
    let mut epoch_str = vec![];
    let mut ric_x_km = vec![];
    let mut ric_y_km = vec![];
    let mut ric_z_km = vec![];
    let mut ric_vx_km_s = vec![];
    let mut ric_vy_km_s = vec![];
    let mut ric_vz_km_s = vec![];

    let mut azimuth_deg = vec![];
    let mut elevation_deg = vec![];
    let mut range_km = vec![];
    let mut range_rate_km_s = vec![];
    for state in trajectory.every(Unit::Minute * 2) {
        // Try to compute the Keplerian/two body state just in time.
        // This method occasionally fails to converge on an appropriate true anomaly
        // from the mean anomaly. If that happens, we just skip this state.
        // The high fidelity and Keplerian states diverge continuously, and we're curious
        // about the divergence in this quick analysis.
        let this_epoch = state.epoch();
        match orbit.at_epoch(this_epoch) {
            Ok(tb_then) => {
                offset_s.push((this_epoch - orbit.epoch).to_seconds());
                epoch_str.push(format!("{this_epoch}"));
                // Compute the two body state just in time.
                let ric = state.orbit.ric_difference(&tb_then)?;
                ric_x_km.push(ric.radius_km.x);
                ric_y_km.push(ric.radius_km.y);
                ric_z_km.push(ric.radius_km.z);
                ric_vx_km_s.push(ric.velocity_km_s.x);
                ric_vy_km_s.push(ric.velocity_km_s.y);
                ric_vz_km_s.push(ric.velocity_km_s.z);

                // Compute the AER data for each state.
                let aer = almanac.azimuth_elevation_range_sez(
                    state.orbit,
                    boulder_station.to_orbit(this_epoch, &almanac)?,
                    None,
                    None,
                )?;
                azimuth_deg.push(aer.azimuth_deg);
                elevation_deg.push(aer.elevation_deg);
                range_km.push(aer.range_km);
                range_rate_km_s.push(aer.range_rate_km_s);
            }
            Err(e) => warn!("{} {e}", state.epoch()),
        };
    }

    // Build the data frames.
    let ric_df = df!(
        "Offset (s)" => offset_s.clone(),
        "Epoch" => epoch_str.clone(),
        "RIC X (km)" => ric_x_km,
        "RIC Y (km)" => ric_y_km,
        "RIC Z (km)" => ric_z_km,
        "RIC VX (km/s)" => ric_vx_km_s,
        "RIC VY (km/s)" => ric_vy_km_s,
        "RIC VZ (km/s)" => ric_vz_km_s,
    )?;

    println!("RIC difference at start\n{}", ric_df.head(Some(10)));
    println!("RIC difference at end\n{}", ric_df.tail(Some(10)));

    let aer_df = df!(
        "Offset (s)" => offset_s.clone(),
        "Epoch" => epoch_str.clone(),
        "azimuth (deg)" => azimuth_deg,
        "elevation (deg)" => elevation_deg,
        "range (km)" => range_km,
        "range rate (km/s)" => range_rate_km_s,
    )?;

    // Finally, let's see when the spacecraft is visible, assuming 15 degrees minimum elevation.
    let mask = aer_df.column("elevation (deg)")?.gt(15.0)?;
    let cubesat_visible = aer_df.filter(&mask)?;

    println!("{cubesat_visible}");

    Ok(())
}

pub fn every_between( &self, step: Duration, start: Epoch, end: Epoch, ) -> TrajIterator<'_, S>

Creates an iterator through the trajectory by the provided step size between the provided bounds

pub fn to_parquet_simple<P: AsRef<Path>>( &self, path: P, almanac: Arc<Almanac>, ) -> Result<PathBuf, Box<dyn Error>>

Store this trajectory arc to a parquet file with the default configuration (depends on the state type, search for export_params in the documentation for details).

pub fn to_parquet_with_cfg<P: AsRef<Path>>( &self, path: P, cfg: ExportCfg, almanac: Arc<Almanac>, ) -> Result<PathBuf, Box<dyn Error>>

Store this trajectory arc to a parquet file with the provided configuration

Examples found in repository

examples/01_orbit_prop/main.rs (lines 183-187)

fn main() -> Result<(), Box<dyn Error>> {
    pel::init();
    // Dynamics models require planetary constants and ephemerides to be defined.
    // Let's start by grabbing those by using ANISE's latest MetaAlmanac.
    // This will automatically download the DE440s planetary ephemeris,
    // the daily-updated Earth Orientation Parameters, the high fidelity Moon orientation
    // parameters (for the Moon Mean Earth and Moon Principal Axes frames), and the PCK11
    // planetary constants kernels.
    // For details, refer to https://github.com/nyx-space/anise/blob/master/data/latest.dhall.
    // Note that we place the Almanac into an Arc so we can clone it cheaply and provide read-only
    // references to many functions.
    let almanac = Arc::new(MetaAlmanac::latest().map_err(Box::new)?);
    // Define the orbit epoch
    let epoch = Epoch::from_gregorian_utc_hms(2024, 2, 29, 12, 13, 14);

    // Define the orbit.
    // First we need to fetch the Earth J2000 from information from the Almanac.
    // This allows the frame to include the gravitational parameters and the shape of the Earth,
    // defined as a tri-axial ellipoid. Note that this shape can be changed manually or in the Almanac
    // by loading a different set of planetary constants.
    let earth_j2000 = almanac.frame_from_uid(EARTH_J2000)?;

    let orbit =
        Orbit::try_keplerian_altitude(300.0, 0.015, 68.5, 65.2, 75.0, 0.0, epoch, earth_j2000)?;
    // Print in in Keplerian form.
    println!("{orbit:x}");

    // There are two ways to propagate an orbit. We can make a quick approximation assuming only two-body
    // motion. This is a useful first order approximation but it isn't used in real-world applications.

    // This approach is a feature of ANISE.
    let future_orbit_tb = orbit.at_epoch(epoch + Unit::Day * 3)?;
    println!("{future_orbit_tb:x}");

    // Two body propagation relies solely on Kepler's laws, so only the true anomaly will change.
    println!(
        "SMA changed by {:.3e} km",
        orbit.sma_km()? - future_orbit_tb.sma_km()?
    );
    println!(
        "ECC changed by {:.3e}",
        orbit.ecc()? - future_orbit_tb.ecc()?
    );
    println!(
        "INC changed by {:.3e} deg",
        orbit.inc_deg()? - future_orbit_tb.inc_deg()?
    );
    println!(
        "RAAN changed by {:.3e} deg",
        orbit.raan_deg()? - future_orbit_tb.raan_deg()?
    );
    println!(
        "AOP changed by {:.3e} deg",
        orbit.aop_deg()? - future_orbit_tb.aop_deg()?
    );
    println!(
        "TA changed by {:.3} deg",
        orbit.ta_deg()? - future_orbit_tb.ta_deg()?
    );

    // Nyx is used for high fidelity propagation, not Keplerian propagation as above.
    // Nyx only propagates Spacecraft at the moment, which allows it to account for acceleration
    // models such as solar radiation pressure.

    // Let's build a cubesat sized spacecraft, with an SRP area of 10 cm^2 and a mass of 9.6 kg.
    let sc = Spacecraft::builder()
        .orbit(orbit)
        .dry_mass_kg(9.60)
        .srp(SrpConfig {
            area_m2: 10e-4,
            cr: 1.1,
        })
        .build();
    println!("{sc:x}");

    // Set up the spacecraft dynamics.

    // Specify that the orbital dynamics must account for the graviational pull of the Moon and the Sun.
    // The gravity of the Earth will also be accounted for since the spaceraft in an Earth orbit.
    let mut orbital_dyn = OrbitalDynamics::point_masses(vec![MOON, SUN]);

    // We want to include the spherical harmonics, so let's download the gravitational data from the Nyx Cloud.
    // We're using the JGM3 model here, which is the default in GMAT.
    let mut jgm3_meta = MetaFile {
        uri: "http://public-data.nyxspace.com/nyx/models/JGM3.cof.gz".to_string(),
        crc32: Some(0xF446F027), // Specifying the CRC32 avoids redownloading it if it's cached.
    };
    // And let's download it if we don't have it yet.
    jgm3_meta.process(true)?;

    // Build the spherical harmonics.
    // The harmonics must be computed in the body fixed frame.
    // We're using the long term prediction of the Earth centered Earth fixed frame, IAU Earth.
    let harmonics_21x21 = Harmonics::from_stor(
        almanac.frame_from_uid(IAU_EARTH_FRAME)?,
        HarmonicsMem::from_cof(&jgm3_meta.uri, 21, 21, true).unwrap(),
    );

    // Include the spherical harmonics into the orbital dynamics.
    orbital_dyn.accel_models.push(harmonics_21x21);

    // We define the solar radiation pressure, using the default solar flux and accounting only
    // for the eclipsing caused by the Earth.
    let srp_dyn = SolarPressure::default(EARTH_J2000, almanac.clone())?;

    // Finalize setting up the dynamics, specifying the force models (orbital_dyn) separately from the
    // acceleration models (SRP in this case). Use `from_models` to specify multiple accel models.
    let dynamics = SpacecraftDynamics::from_model(orbital_dyn, srp_dyn);

    println!("{dynamics}");

    // Finally, let's propagate this orbit to the same epoch as above.
    // The first returned value is the spacecraft state at the final epoch.
    // The second value is the full trajectory where the step size is variable step used by the propagator.
    let (future_sc, trajectory) = Propagator::default(dynamics)
        .with(sc, almanac.clone())
        .until_epoch_with_traj(future_orbit_tb.epoch)?;

    println!("=== High fidelity propagation ===");
    println!(
        "SMA changed by {:.3} km",
        orbit.sma_km()? - future_sc.orbit.sma_km()?
    );
    println!(
        "ECC changed by {:.6}",
        orbit.ecc()? - future_sc.orbit.ecc()?
    );
    println!(
        "INC changed by {:.3e} deg",
        orbit.inc_deg()? - future_sc.orbit.inc_deg()?
    );
    println!(
        "RAAN changed by {:.3} deg",
        orbit.raan_deg()? - future_sc.orbit.raan_deg()?
    );
    println!(
        "AOP changed by {:.3} deg",
        orbit.aop_deg()? - future_sc.orbit.aop_deg()?
    );
    println!(
        "TA changed by {:.3} deg",
        orbit.ta_deg()? - future_sc.orbit.ta_deg()?
    );

    // We also have access to the full trajectory throughout the propagation.
    println!("{trajectory}");

    // With the trajectory, let's build a few data products.

    // 1. Export the trajectory as a CCSDS OEM version 2.0 file and as a parquet file, which includes the Keplerian orbital elements.

    trajectory.to_oem_file(
        "./01_cubesat_hf_prop.oem",
        ExportCfg::builder().step(Unit::Minute * 2).build(),
    )?;

    trajectory.to_parquet_with_cfg(
        "./01_cubesat_hf_prop.parquet",
        ExportCfg::builder().step(Unit::Minute * 2).build(),
        almanac.clone(),
    )?;

    // 2. Compare the difference in the radial-intrack-crosstrack frame between the high fidelity
    // and Keplerian propagation. The RIC frame is commonly used to compute the difference in position
    // and velocity of different spacecraft.
    // 3. Compute the azimuth, elevation, range, and range-rate data of that spacecraft as seen from Boulder, CO, USA.

    let boulder_station = GroundStation::from_point(
        "Boulder, CO, USA".to_string(),
        40.014984,   // latitude in degrees
        -105.270546, // longitude in degrees
        1.6550,      // altitude in kilometers
        almanac.frame_from_uid(IAU_EARTH_FRAME)?,
    );

    // We iterate over the trajectory, grabbing a state every two minutes.
    let mut offset_s = vec![];
    let mut epoch_str = vec![];
    let mut ric_x_km = vec![];
    let mut ric_y_km = vec![];
    let mut ric_z_km = vec![];
    let mut ric_vx_km_s = vec![];
    let mut ric_vy_km_s = vec![];
    let mut ric_vz_km_s = vec![];

    let mut azimuth_deg = vec![];
    let mut elevation_deg = vec![];
    let mut range_km = vec![];
    let mut range_rate_km_s = vec![];
    for state in trajectory.every(Unit::Minute * 2) {
        // Try to compute the Keplerian/two body state just in time.
        // This method occasionally fails to converge on an appropriate true anomaly
        // from the mean anomaly. If that happens, we just skip this state.
        // The high fidelity and Keplerian states diverge continuously, and we're curious
        // about the divergence in this quick analysis.
        let this_epoch = state.epoch();
        match orbit.at_epoch(this_epoch) {
            Ok(tb_then) => {
                offset_s.push((this_epoch - orbit.epoch).to_seconds());
                epoch_str.push(format!("{this_epoch}"));
                // Compute the two body state just in time.
                let ric = state.orbit.ric_difference(&tb_then)?;
                ric_x_km.push(ric.radius_km.x);
                ric_y_km.push(ric.radius_km.y);
                ric_z_km.push(ric.radius_km.z);
                ric_vx_km_s.push(ric.velocity_km_s.x);
                ric_vy_km_s.push(ric.velocity_km_s.y);
                ric_vz_km_s.push(ric.velocity_km_s.z);

                // Compute the AER data for each state.
                let aer = almanac.azimuth_elevation_range_sez(
                    state.orbit,
                    boulder_station.to_orbit(this_epoch, &almanac)?,
                    None,
                    None,
                )?;
                azimuth_deg.push(aer.azimuth_deg);
                elevation_deg.push(aer.elevation_deg);
                range_km.push(aer.range_km);
                range_rate_km_s.push(aer.range_rate_km_s);
            }
            Err(e) => warn!("{} {e}", state.epoch()),
        };
    }

    // Build the data frames.
    let ric_df = df!(
        "Offset (s)" => offset_s.clone(),
        "Epoch" => epoch_str.clone(),
        "RIC X (km)" => ric_x_km,
        "RIC Y (km)" => ric_y_km,
        "RIC Z (km)" => ric_z_km,
        "RIC VX (km/s)" => ric_vx_km_s,
        "RIC VY (km/s)" => ric_vy_km_s,
        "RIC VZ (km/s)" => ric_vz_km_s,
    )?;

    println!("RIC difference at start\n{}", ric_df.head(Some(10)));
    println!("RIC difference at end\n{}", ric_df.tail(Some(10)));

    let aer_df = df!(
        "Offset (s)" => offset_s.clone(),
        "Epoch" => epoch_str.clone(),
        "azimuth (deg)" => azimuth_deg,
        "elevation (deg)" => elevation_deg,
        "range (km)" => range_km,
        "range rate (km/s)" => range_rate_km_s,
    )?;

    // Finally, let's see when the spacecraft is visible, assuming 15 degrees minimum elevation.
    let mask = aer_df.column("elevation (deg)")?.gt(15.0)?;
    let cubesat_visible = aer_df.filter(&mask)?;

    println!("{cubesat_visible}");

    Ok(())
}

pub fn to_parquet<P: AsRef<Path>>( &self, path: P, events: Option<Vec<&dyn EventEvaluator<S>>>, cfg: ExportCfg, almanac: Arc<Almanac>, ) -> Result<PathBuf, Box<dyn Error>>

Store this trajectory arc to a parquet file with the provided configuration and event evaluators

Examples found in repository

examples/03_geo_analysis/raise.rs (lines 133-140)

fn main() -> Result<(), Box<dyn Error>> {
    pel::init();

    // Dynamics models require planetary constants and ephemerides to be defined.
    // Let's start by grabbing those by using ANISE's latest MetaAlmanac.
    // This will automatically download the DE440s planetary ephemeris,
    // the daily-updated Earth Orientation Parameters, the high fidelity Moon orientation
    // parameters (for the Moon Mean Earth and Moon Principal Axes frames), and the PCK11
    // planetary constants kernels.
    // For details, refer to https://github.com/nyx-space/anise/blob/master/data/latest.dhall.
    // Note that we place the Almanac into an Arc so we can clone it cheaply and provide read-only
    // references to many functions.
    let almanac = Arc::new(MetaAlmanac::latest().map_err(Box::new)?);
    // Fetch the EME2000 frame from the Almabac
    let eme2k = almanac.frame_from_uid(EARTH_J2000).unwrap();
    // Define the orbit epoch
    let epoch = Epoch::from_gregorian_utc_hms(2024, 2, 29, 12, 13, 14);

    // Build the spacecraft itself.
    // Using slide 6 of https://aerospace.org/sites/default/files/2018-11/Davis-Mayberry_HPSEP_11212018.pdf
    // for the "next gen" SEP characteristics.

    // GTO start
    let orbit = Orbit::keplerian(24505.9, 0.725, 7.05, 0.0, 0.0, 0.0, epoch, eme2k);

    let sc = Spacecraft::builder()
        .orbit(orbit)
        .dry_mass_kg(1000.0) // 1000 kg of dry mass
        .fuel_mass_kg(1000.0) // 1000 kg of fuel, totalling 2.0 tons
        .srp(SrpConfig::from_area(3.0 * 6.0)) // Assuming 1 kW/m^2 or 18 kW, giving a margin of 4.35 kW for on-propulsion consumption
        .thruster(Thruster {
            // "NEXT-STEP" row in Table 2
            isp_s: 4435.0,
            thrust_N: 0.472,
        })
        .mode(GuidanceMode::Thrust) // Start thrusting immediately.
        .build();

    let prop_time = 180.0 * Unit::Day;

    // Define the guidance law -- we're just using a Ruggiero controller as demonstrated in AAS-2004-5089.
    let objectives = &[
        Objective::within_tolerance(StateParameter::SMA, 42_165.0, 20.0),
        Objective::within_tolerance(StateParameter::Eccentricity, 0.001, 5e-5),
        Objective::within_tolerance(StateParameter::Inclination, 0.05, 1e-2),
    ];

    // Ensure that we only thrust if we have more than 20% illumination.
    let ruggiero_ctrl = Ruggiero::from_max_eclipse(objectives, sc, 0.2).unwrap();
    println!("{ruggiero_ctrl}");

    // Define the high fidelity dynamics

    // Set up the spacecraft dynamics.

    // Specify that the orbital dynamics must account for the graviational pull of the Moon and the Sun.
    // The gravity of the Earth will also be accounted for since the spaceraft in an Earth orbit.
    let mut orbital_dyn = OrbitalDynamics::point_masses(vec![MOON, SUN]);

    // We want to include the spherical harmonics, so let's download the gravitational data from the Nyx Cloud.
    // We're using the JGM3 model here, which is the default in GMAT.
    let mut jgm3_meta = MetaFile {
        uri: "http://public-data.nyxspace.com/nyx/models/JGM3.cof.gz".to_string(),
        crc32: Some(0xF446F027), // Specifying the CRC32 avoids redownloading it if it's cached.
    };
    // And let's download it if we don't have it yet.
    jgm3_meta.process(true)?;

    // Build the spherical harmonics.
    // The harmonics must be computed in the body fixed frame.
    // We're using the long term prediction of the Earth centered Earth fixed frame, IAU Earth.
    let harmonics = Harmonics::from_stor(
        almanac.frame_from_uid(IAU_EARTH_FRAME)?,
        HarmonicsMem::from_cof(&jgm3_meta.uri, 8, 8, true).unwrap(),
    );

    // Include the spherical harmonics into the orbital dynamics.
    orbital_dyn.accel_models.push(harmonics);

    // We define the solar radiation pressure, using the default solar flux and accounting only
    // for the eclipsing caused by the Earth.
    let srp_dyn = SolarPressure::default(EARTH_J2000, almanac.clone())?;

    // Finalize setting up the dynamics, specifying the force models (orbital_dyn) separately from the
    // acceleration models (SRP in this case). Use `from_models` to specify multiple accel models.
    let sc_dynamics = SpacecraftDynamics::from_model(orbital_dyn, srp_dyn)
        .with_guidance_law(ruggiero_ctrl.clone());

    println!("{:x}", orbit);

    // We specify a minimum step in the propagator because the Ruggiero control would otherwise drive this step very low.
    let (final_state, traj) = Propagator::rk89(
        sc_dynamics.clone(),
        IntegratorOptions::builder()
            .min_step(10.0_f64.seconds())
            .error_ctrl(ErrorControl::RSSCartesianStep)
            .build(),
    )
    .with(sc, almanac.clone())
    .for_duration_with_traj(prop_time)?;

    let fuel_usage = sc.fuel_mass_kg - final_state.fuel_mass_kg;
    println!("{:x}", final_state.orbit);
    println!("fuel usage: {:.3} kg", fuel_usage);

    // Finally, export the results for analysis, including the penumbra percentage throughout the orbit raise.
    traj.to_parquet(
        "./03_geo_raise.parquet",
        Some(vec![
            &EclipseLocator::cislunar(almanac.clone()).to_penumbra_event()
        ]),
        ExportCfg::default(),
        almanac,
    )?;

    for status_line in ruggiero_ctrl.status(&final_state) {
        println!("{status_line}");
    }

    ruggiero_ctrl
        .achieved(&final_state)
        .expect("objective not achieved");

    Ok(())
}

examples/03_geo_analysis/drift.rs (lines 152-159)

fn main() -> Result<(), Box<dyn Error>> {
    pel::init();
    // Dynamics models require planetary constants and ephemerides to be defined.
    // Let's start by grabbing those by using ANISE's latest MetaAlmanac.
    // This will automatically download the DE440s planetary ephemeris,
    // the daily-updated Earth Orientation Parameters, the high fidelity Moon orientation
    // parameters (for the Moon Mean Earth and Moon Principal Axes frames), and the PCK11
    // planetary constants kernels.
    // For details, refer to https://github.com/nyx-space/anise/blob/master/data/latest.dhall.
    // Note that we place the Almanac into an Arc so we can clone it cheaply and provide read-only
    // references to many functions.
    let almanac = Arc::new(MetaAlmanac::latest().map_err(Box::new)?);
    // Define the orbit epoch
    let epoch = Epoch::from_gregorian_utc_hms(2024, 2, 29, 12, 13, 14);

    // Define the orbit.
    // First we need to fetch the Earth J2000 from information from the Almanac.
    // This allows the frame to include the gravitational parameters and the shape of the Earth,
    // defined as a tri-axial ellipoid. Note that this shape can be changed manually or in the Almanac
    // by loading a different set of planetary constants.
    let earth_j2000 = almanac.frame_from_uid(EARTH_J2000)?;

    // Placing this GEO bird just above Colorado.
    // In theory, the eccentricity is zero, but in practice, it's about 1e-5 to 1e-6 at best.
    let orbit = Orbit::try_keplerian(42164.0, 1e-5, 0., 163.0, 75.0, 0.0, epoch, earth_j2000)?;
    // Print in in Keplerian form.
    println!("{orbit:x}");

    let state_bf = almanac.transform_to(orbit, IAU_EARTH_FRAME, None)?;
    let (orig_lat_deg, orig_long_deg, orig_alt_km) = state_bf.latlongalt()?;

    // Nyx is used for high fidelity propagation, not Keplerian propagation as above.
    // Nyx only propagates Spacecraft at the moment, which allows it to account for acceleration
    // models such as solar radiation pressure.

    // Let's build a cubesat sized spacecraft, with an SRP area of 10 cm^2 and a mass of 9.6 kg.
    let sc = Spacecraft::builder()
        .orbit(orbit)
        .dry_mass_kg(9.60)
        .srp(SrpConfig {
            area_m2: 10e-4,
            cr: 1.1,
        })
        .build();
    println!("{sc:x}");

    // Set up the spacecraft dynamics.

    // Specify that the orbital dynamics must account for the graviational pull of the Moon and the Sun.
    // The gravity of the Earth will also be accounted for since the spaceraft in an Earth orbit.
    let mut orbital_dyn = OrbitalDynamics::point_masses(vec![MOON, SUN]);

    // We want to include the spherical harmonics, so let's download the gravitational data from the Nyx Cloud.
    // We're using the JGM3 model here, which is the default in GMAT.
    let mut jgm3_meta = MetaFile {
        uri: "http://public-data.nyxspace.com/nyx/models/JGM3.cof.gz".to_string(),
        crc32: Some(0xF446F027), // Specifying the CRC32 avoids redownloading it if it's cached.
    };
    // And let's download it if we don't have it yet.
    jgm3_meta.process(true)?;

    // Build the spherical harmonics.
    // The harmonics must be computed in the body fixed frame.
    // We're using the long term prediction of the Earth centered Earth fixed frame, IAU Earth.
    let harmonics_21x21 = Harmonics::from_stor(
        almanac.frame_from_uid(IAU_EARTH_FRAME)?,
        HarmonicsMem::from_cof(&jgm3_meta.uri, 21, 21, true).unwrap(),
    );

    // Include the spherical harmonics into the orbital dynamics.
    orbital_dyn.accel_models.push(harmonics_21x21);

    // We define the solar radiation pressure, using the default solar flux and accounting only
    // for the eclipsing caused by the Earth and Moon.
    let srp_dyn = SolarPressure::new(vec![EARTH_J2000, MOON_J2000], almanac.clone())?;

    // Finalize setting up the dynamics, specifying the force models (orbital_dyn) separately from the
    // acceleration models (SRP in this case). Use `from_models` to specify multiple accel models.
    let dynamics = SpacecraftDynamics::from_model(orbital_dyn, srp_dyn);

    println!("{dynamics}");

    // Finally, let's propagate this orbit to the same epoch as above.
    // The first returned value is the spacecraft state at the final epoch.
    // The second value is the full trajectory where the step size is variable step used by the propagator.
    let (future_sc, trajectory) = Propagator::default(dynamics)
        .with(sc, almanac.clone())
        .until_epoch_with_traj(epoch + Unit::Century * 0.03)?;

    println!("=== High fidelity propagation ===");
    println!(
        "SMA changed by {:.3} km",
        orbit.sma_km()? - future_sc.orbit.sma_km()?
    );
    println!(
        "ECC changed by {:.6}",
        orbit.ecc()? - future_sc.orbit.ecc()?
    );
    println!(
        "INC changed by {:.3e} deg",
        orbit.inc_deg()? - future_sc.orbit.inc_deg()?
    );
    println!(
        "RAAN changed by {:.3} deg",
        orbit.raan_deg()? - future_sc.orbit.raan_deg()?
    );
    println!(
        "AOP changed by {:.3} deg",
        orbit.aop_deg()? - future_sc.orbit.aop_deg()?
    );
    println!(
        "TA changed by {:.3} deg",
        orbit.ta_deg()? - future_sc.orbit.ta_deg()?
    );

    // We also have access to the full trajectory throughout the propagation.
    println!("{trajectory}");

    println!("Spacecraft params after 3 years without active control:\n{future_sc:x}");

    // With the trajectory, let's build a few data products.

    // 1. Export the trajectory as a parquet file, which includes the Keplerian orbital elements.

    let analysis_step = Unit::Minute * 5;

    trajectory.to_parquet(
        "./03_geo_hf_prop.parquet",
        Some(vec![
            &EclipseLocator::cislunar(almanac.clone()).to_penumbra_event()
        ]),
        ExportCfg::builder().step(analysis_step).build(),
        almanac.clone(),
    )?;

    // 2. Compute the latitude, longitude, and altitude throughout the trajectory by rotating the spacecraft position into the Earth body fixed frame.

    // We iterate over the trajectory, grabbing a state every two minutes.
    let mut offset_s = vec![];
    let mut epoch_str = vec![];
    let mut longitude_deg = vec![];
    let mut latitude_deg = vec![];
    let mut altitude_km = vec![];

    for state in trajectory.every(analysis_step) {
        // Convert the GEO bird state into the body fixed frame, and keep track of its latitude, longitude, and altitude.
        // These define the GEO stationkeeping box.

        let this_epoch = state.epoch();

        offset_s.push((this_epoch - orbit.epoch).to_seconds());
        epoch_str.push(this_epoch.to_isoformat());

        let state_bf = almanac.transform_to(state.orbit, IAU_EARTH_FRAME, None)?;
        let (lat_deg, long_deg, alt_km) = state_bf.latlongalt()?;
        longitude_deg.push(long_deg);
        latitude_deg.push(lat_deg);
        altitude_km.push(alt_km);
    }

    println!(
        "Longitude changed by {:.3} deg -- Box is 0.1 deg E-W",
        orig_long_deg - longitude_deg.last().unwrap()
    );

    println!(
        "Latitude changed by {:.3} deg -- Box is 0.05 deg N-S",
        orig_lat_deg - latitude_deg.last().unwrap()
    );

    println!(
        "Altitude changed by {:.3} km -- Box is 30 km",
        orig_alt_km - altitude_km.last().unwrap()
    );

    // Build the station keeping data frame.
    let mut sk_df = df!(
        "Offset (s)" => offset_s.clone(),
        "Epoch (UTC)" => epoch_str.clone(),
        "Longitude E-W (deg)" => longitude_deg,
        "Latitude N-S (deg)" => latitude_deg,
        "Altitude (km)" => altitude_km,

    )?;

    // Create a file to write the Parquet to
    let file = File::create("./03_geo_lla.parquet").expect("Could not create file");

    // Create a ParquetWriter and write the DataFrame to the file
    ParquetWriter::new(file).finish(&mut sk_df)?;

    Ok(())
}

pub fn resample(&self, step: Duration) -> Result<Self, NyxError>

Allows resampling this trajectory at a fixed interval instead of using the propagator step size. This may lead to aliasing due to the Nyquist–Shannon sampling theorem.

pub fn rebuild(&self, epochs: &[Epoch]) -> Result<Self, NyxError>

Rebuilds this trajectory with the provided epochs. This may lead to aliasing due to the Nyquist–Shannon sampling theorem.

pub fn ric_diff_to_parquet<P: AsRef<Path>>( &self, other: &Self, path: P, cfg: ExportCfg, ) -> Result<PathBuf, Box<dyn Error>>

Export the difference in RIC from of this trajectory compare to the “other” trajectory in parquet format.

Notes

• The RIC frame accounts for the transport theorem by performing a finite differencing of the RIC frame.

Examples found in repository

examples/04_lro_od/main.rs (lines 173-177)

fn main() -> Result<(), Box<dyn Error>> {
    pel::init();

    // ====================== //
    // === ALMANAC SET UP === //
    // ====================== //

    // Dynamics models require planetary constants and ephemerides to be defined.
    // Let's start by grabbing those by using ANISE's MetaAlmanac.

    let data_folder: PathBuf = [env!("CARGO_MANIFEST_DIR"), "examples", "04_lro_od"]
        .iter()
        .collect();

    let meta = data_folder.join("lro-dynamics.dhall");

    // Load this ephem in the general Almanac we're using for this analysis.
    let mut almanac = MetaAlmanac::new(meta.to_string_lossy().to_string())
        .map_err(Box::new)?
        .process(true)
        .map_err(Box::new)?;

    let mut moon_pc = almanac.planetary_data.get_by_id(MOON)?;
    moon_pc.mu_km3_s2 = 4902.74987;
    almanac.planetary_data.set_by_id(MOON, moon_pc)?;

    let mut earth_pc = almanac.planetary_data.get_by_id(EARTH)?;
    earth_pc.mu_km3_s2 = 398600.436;
    almanac.planetary_data.set_by_id(EARTH, earth_pc)?;

    // Save this new kernel for reuse.
    // In an operational context, this would be part of the "Lock" process, and should not change throughout the mission.
    almanac
        .planetary_data
        .save_as(&data_folder.join("lro-specific.pca"), true)?;

    // Lock the almanac (an Arc is a read only structure).
    let almanac = Arc::new(almanac);

    // Orbit determination requires a Trajectory structure, which can be saved as parquet file.
    // In our case, the trajectory comes from the BSP file, so we need to build a Trajectory from the almanac directly.
    // To query the Almanac, we need to build the LRO frame in the J2000 orientation in our case.
    // Inspecting the LRO BSP in the ANISE GUI shows us that NASA has assigned ID -85 to LRO.
    let lro_frame = Frame::from_ephem_j2000(-85);

    // To build the trajectory we need to provide a spacecraft template.
    let sc_template = Spacecraft::builder()
        .dry_mass_kg(1018.0) // Launch masses
        .fuel_mass_kg(900.0)
        .srp(SrpConfig {
            // SRP configuration is arbitrary, but we will be estimating it anyway.
            area_m2: 3.9 * 2.7,
            cr: 0.96,
        })
        .orbit(Orbit::zero(MOON_J2000)) // Setting a zero orbit here because it's just a template
        .build();
    // Now we can build the trajectory from the BSP file.
    // We'll arbitrarily set the tracking arc to 48 hours with a one minute time step.
    let traj_as_flown = Traj::from_bsp(
        lro_frame,
        MOON_J2000,
        almanac.clone(),
        sc_template,
        5.seconds(),
        Some(Epoch::from_str("2024-01-01 00:00:00 UTC")?),
        Some(Epoch::from_str("2024-01-02 00:00:00 UTC")?),
        Aberration::LT,
        Some("LRO".to_string()),
    )?;

    println!("{traj_as_flown}");

    // ====================== //
    // === MODEL MATCHING === //
    // ====================== //

    // Set up the spacecraft dynamics.

    // Specify that the orbital dynamics must account for the graviational pull of the Earth and the Sun.
    // The gravity of the Moon will also be accounted for since the spaceraft in a lunar orbit.
    let mut orbital_dyn = OrbitalDynamics::point_masses(vec![EARTH, SUN, JUPITER_BARYCENTER]);

    // We want to include the spherical harmonics, so let's download the gravitational data from the Nyx Cloud.
    // We're using the GRAIL JGGRX model.
    let mut jggrx_meta = MetaFile {
        uri: "http://public-data.nyxspace.com/nyx/models/Luna_jggrx_1500e_sha.tab.gz".to_string(),
        crc32: Some(0x6bcacda8), // Specifying the CRC32 avoids redownloading it if it's cached.
    };
    // And let's download it if we don't have it yet.
    jggrx_meta.process(true)?;

    // Build the spherical harmonics.
    // The harmonics must be computed in the body fixed frame.
    // We're using the long term prediction of the Moon principal axes frame.
    let moon_pa_frame = MOON_PA_FRAME.with_orient(31008);
    // let moon_pa_frame = IAU_MOON_FRAME;
    let sph_harmonics = Harmonics::from_stor(
        almanac.frame_from_uid(moon_pa_frame)?,
        HarmonicsMem::from_shadr(&jggrx_meta.uri, 80, 80, true)?,
    );

    // Include the spherical harmonics into the orbital dynamics.
    orbital_dyn.accel_models.push(sph_harmonics);

    // We define the solar radiation pressure, using the default solar flux and accounting only
    // for the eclipsing caused by the Earth and Moon.
    // Note that by default, enabling the SolarPressure model will also enable the estimation of the coefficient of reflectivity.
    let srp_dyn = SolarPressure::new(vec![EARTH_J2000, MOON_J2000], almanac.clone())?;

    // Finalize setting up the dynamics, specifying the force models (orbital_dyn) separately from the
    // acceleration models (SRP in this case). Use `from_models` to specify multiple accel models.
    let dynamics = SpacecraftDynamics::from_model(orbital_dyn, srp_dyn);

    println!("{dynamics}");

    // Now we can build the propagator.
    let setup = Propagator::default_dp78(dynamics.clone());

    // For reference, let's build the trajectory with Nyx's models from that LRO state.
    let (sim_final, traj_as_sim) = setup
        .with(*traj_as_flown.first(), almanac.clone())
        .until_epoch_with_traj(traj_as_flown.last().epoch())?;

    println!("SIM INIT:  {:x}", traj_as_flown.first());
    println!("SIM FINAL: {sim_final:x}");
    // Compute RIC difference between SIM and LRO ephem
    let sim_lro_delta = sim_final
        .orbit
        .ric_difference(&traj_as_flown.last().orbit)?;
    println!("{traj_as_sim}");
    println!(
        "SIM v LRO - RIC Position (m): {:.3}",
        sim_lro_delta.radius_km * 1e3
    );
    println!(
        "SIM v LRO - RIC Velocity (m/s): {:.3}",
        sim_lro_delta.velocity_km_s * 1e3
    );

    traj_as_sim.ric_diff_to_parquet(
        &traj_as_flown,
        "./04_lro_sim_truth_error.parquet",
        ExportCfg::default(),
    )?;

    // ==================== //
    // === OD SIMULATOR === //
    // ==================== //

    // After quite some time trying to exactly match the model, we still end up with an oscillatory difference on the order of 150 meters between the propagated state
    // and the truth LRO state.

    // Therefore, we will actually run an estimation from a dispersed LRO state.
    // The sc_seed is the true LRO state from the BSP.
    let sc_seed = *traj_as_flown.first();

    // Load the Deep Space Network ground stations.
    // Nyx allows you to build these at runtime but it's pretty static so we can just load them from YAML.
    let ground_station_file: PathBuf = [
        env!("CARGO_MANIFEST_DIR"),
        "examples",
        "04_lro_od",
        "dsn-network.yaml",
    ]
    .iter()
    .collect();

    let devices = GroundStation::load_many(ground_station_file)?;

    // Typical OD software requires that you specify your own tracking schedule or you'll have overlapping measurements.
    // Nyx can build a tracking schedule for you based on the first station with access.
    let trkconfg_yaml: PathBuf = [
        env!("CARGO_MANIFEST_DIR"),
        "examples",
        "04_lro_od",
        "tracking-cfg.yaml",
    ]
    .iter()
    .collect();

    let configs: BTreeMap<String, TrkConfig> = TrkConfig::load_named(trkconfg_yaml)?;

    // Build the tracking arc simulation to generate a "standard measurement".
    let mut trk = TrackingArcSim::<Spacecraft, RangeDoppler, _>::new(
        devices,
        traj_as_flown.clone(),
        configs,
    )?;

    trk.build_schedule(almanac.clone())?;
    let arc = trk.generate_measurements(almanac.clone())?;
    // Save the simulated tracking data
    arc.to_parquet_simple("./04_lro_simulated_tracking.parquet")?;

    // We'll note that in our case, we have continuous coverage of LRO when the vehicle is not behind the Moon.
    println!("{arc}");

    // Now that we have simulated measurements, we'll run the orbit determination.

    // ===================== //
    // === OD ESTIMATION === //
    // ===================== //

    let sc = SpacecraftUncertainty::builder()
        .nominal(sc_seed)
        .frame(LocalFrame::RIC)
        .x_km(0.5)
        .y_km(0.5)
        .z_km(0.5)
        .vx_km_s(5e-3)
        .vy_km_s(5e-3)
        .vz_km_s(5e-3)
        .build();

    // Build the filter initial estimate, which we will reuse in the filter.
    let initial_estimate = sc.to_estimate()?;

    println!("== FILTER STATE ==\n{sc_seed:x}\n{initial_estimate}");

    let kf = KF::new(
        // Increase the initial covariance to account for larger deviation.
        initial_estimate,
        // Until https://github.com/nyx-space/nyx/issues/351, we need to specify the SNC in the acceleration of the Moon J2000 frame.
        SNC3::from_diagonal(10 * Unit::Minute, &[1e-11, 1e-11, 1e-11]),
    );

    // We'll set up the OD process to reject measurements whose residuals are mover than 4 sigmas away from what we expect.
    let mut odp = ODProcess::ckf(
        setup.with(initial_estimate.state().with_stm(), almanac.clone()),
        kf,
        Some(ResidRejectCrit::default()),
        almanac.clone(),
    );

    odp.process_arc::<GroundStation>(&arc)?;

    let ric_err = traj_as_flown
        .at(odp.estimates.last().unwrap().epoch())?
        .orbit
        .ric_difference(&odp.estimates.last().unwrap().orbital_state())?;
    println!("== RIC at end ==");
    println!("RIC Position (m): {}", ric_err.radius_km * 1e3);
    println!("RIC Velocity (m/s): {}", ric_err.velocity_km_s * 1e3);

    odp.to_parquet("./04_lro_od_results.parquet", ExportCfg::default())?;

    // In our case, we have the truth trajectory from NASA.
    // So we can compute the RIC state difference between the real LRO ephem and what we've just estimated.
    // Export the OD trajectory first.
    let od_trajectory = odp.to_traj()?;
    // Build the RIC difference.
    od_trajectory.ric_diff_to_parquet(
        &traj_as_flown,
        "./04_lro_od_truth_error.parquet",
        ExportCfg::default(),
    )?;

    Ok(())
}

impl<S: Interpolatable> Traj<S>

where DefaultAllocator: Allocator<S::VecLength> + Allocator<S::Size> + Allocator<S::Size, S::Size>,

pub fn find_bracketed<E>( &self, start: Epoch, end: Epoch, event: &E, almanac: Arc<Almanac>, ) -> Result<EventDetails<S>, EventError>

where E: EventEvaluator<S>,

Find the exact state where the request event happens. The event function is expected to be monotone in the provided interval because we find the event using a Brent solver.

pub fn find<E>( &self, event: &E, almanac: Arc<Almanac>, ) -> Result<Vec<EventDetails<S>>, EventError>

where E: EventEvaluator<S>,

Find all of the states where the event happens

Limitations

This method uses a Brent solver. If the function that defines the event is not unimodal, the event finder may not converge correctly.

Heuristic detail

The initial search step is 1% of the duration of the trajectory duration. For example, if the trajectory is 100 days long, then we split the trajectory into 100 chunks of 1 day and see whether the event is in there. If the event happens twice or more times within 1% of the trajectory duration, only the one of such events will be found.

If this heuristic fails to find any such events, then find_minmax is called on the event with a time precision of Unit::Second. Then we search only within the min and max bounds of the provided event.

pub fn find_minmax<E>( &self, event: &E, precision: Unit, almanac: Arc<Almanac>, ) -> Result<(S, S), EventError>

where E: EventEvaluator<S>,

Find the minimum and maximum of the provided event through the trajectory

pub fn find_arcs<E>( &self, event: &E, almanac: Arc<Almanac>, ) -> Result<Vec<EventArc<S>>, EventError>

where E: EventEvaluator<S>,

Identifies and pairs rising and falling edge events in a trajectory.

This function processes a sequence of events in a trajectory and pairs each rising edge event with its subsequent falling edge event to form arcs. Each arc represents a complete cycle of an event rising above and then falling below a specified threshold. Use this to analyze a trajectory’s behavior when understanding the complete cycle of an event (from rising to falling) is essential, e.g. ground station passes.

Arguments

• event: A reference to an object implementing the EventEvaluator<S> trait, which is used to evaluate and classify events in the trajectory.

Returns

• Result<Vec<EventArc>, NyxError>: On success, returns a vector of EventArc, where each struct contains a pair of EventDetails (one for the rising edge and one for the falling edge). Returns an error if any issues occur during the event evaluation process.

Logic

• Sorts the events by their epoch to ensure chronological processing.
• Iterates through the sorted events, identifying transitions from falling to rising edges and vice versa.
• Pairs a rising edge with the subsequent falling edge to form an arc.
• Handles edge cases where the trajectory starts or ends with a rising or falling edge.
• Prints debug information for each event and arc.

Note

If no zero crossing happens in the trajectory, i.e. the there is “event is true” and “event is false”, then this function checks whether the event is true at the start and end of the trajectory. If so, it means that there is a single arc that spans the whole trajectory.

Trait Implementations

impl<S: Interpolatable> Add<&Traj<S>> for &Traj<S>

where DefaultAllocator: Allocator<S::VecLength> + Allocator<S::Size> + Allocator<S::Size, S::Size>,

fn add(self, other: &Traj<S>) -> Self::Output

Add one trajectory to another, returns an error if the frames don’t match

type Output = Result<Traj<S>, NyxError>

The resulting type after applying the + operator.

impl<S: Interpolatable> Add for Traj<S>

where DefaultAllocator: Allocator<S::VecLength> + Allocator<S::Size> + Allocator<S::Size, S::Size>,

fn add(self, other: Traj<S>) -> Self::Output

Add one trajectory to another. If they do not overlap to within 10ms, a warning will be printed.

type Output = Result<Traj<S>, NyxError>

The resulting type after applying the + operator.

impl<S: Interpolatable> AddAssign<&Traj<S>> for Traj<S>

where DefaultAllocator: Allocator<S::VecLength> + Allocator<S::Size> + Allocator<S::Size, S::Size>,

fn add_assign(&mut self, rhs: &Self)

Attempt to add two trajectories together and assign it to self

Warnings

1. This will panic if the frames mismatch!
2. This is inefficient because both self and rhs are cloned.

impl<S: Clone + Interpolatable> Clone for Traj<S>

where DefaultAllocator: Allocator<S::VecLength> + Allocator<S::Size> + Allocator<S::Size, S::Size>,

fn clone(&self) -> Traj<S>

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<S: Interpolatable> Debug for Traj<S>

where DefaultAllocator: Allocator<S::VecLength> + Allocator<S::Size> + Allocator<S::Size, S::Size>,

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<S: Interpolatable> Default for Traj<S>

where DefaultAllocator: Allocator<S::VecLength> + Allocator<S::Size> + Allocator<S::Size, S::Size>,

fn default() -> Self

Returns the “default value” for a type.

impl<S: Interpolatable> Display for Traj<S>

where DefaultAllocator: Allocator<S::VecLength> + Allocator<S::Size> + Allocator<S::Size, S::Size>,

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<S: PartialEq + Interpolatable> PartialEq for Traj<S>

where DefaultAllocator: Allocator<S::VecLength> + Allocator<S::Size> + Allocator<S::Size, S::Size>,

fn eq(&self, other: &Traj<S>) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl<S: Interpolatable> StructuralPartialEq for Traj<S>

where DefaultAllocator: Allocator<S::VecLength> + Allocator<S::Size> + Allocator<S::Size, S::Size>,