Struct TrackingArcSim 

pub struct TrackingArcSim<MsrIn, D>
where
    D: TrackingDevice<MsrIn>,
    MsrIn: State + Interpolatable,
    DefaultAllocator: Allocator<<MsrIn as State>::Size> + Allocator<<MsrIn as State>::Size, <MsrIn as State>::Size> + Allocator<<MsrIn as State>::VecLength>,
{
    pub devices: BTreeMap<String, D>,
    pub trajectory: Traj<MsrIn>,
    pub configs: BTreeMap<String, TrkConfig>,
    /* private fields */
}

Fields

devices: BTreeMap<String, D>

Map of devices from their names.

trajectory: Traj<MsrIn>

Receiver trajectory

configs: BTreeMap<String, TrkConfig>

Configuration of each device

Implementations

impl<MsrIn, D> TrackingArcSim<MsrIn, D>

where D: TrackingDevice<MsrIn>, MsrIn: State + Interpolatable, DefaultAllocator: Allocator<<MsrIn as State>::Size> + Allocator<<MsrIn as State>::Size, <MsrIn as State>::Size> + Allocator<<MsrIn as State>::VecLength>,

pub fn with_rng( devices: BTreeMap<String, D>, trajectory: Traj<MsrIn>, configs: BTreeMap<String, TrkConfig>, rng: Pcg64Mcg, ) -> Result<Self, ConfigError>

Build a new tracking arc simulator using the provided seeded random number generator.

pub fn with_seed( devices: BTreeMap<String, D>, trajectory: Traj<MsrIn>, configs: BTreeMap<String, TrkConfig>, seed: u64, ) -> Result<Self, ConfigError>

Build a new tracking arc simulator using the provided seed to initialize the random number generator.

Examples found in repository

examples/05_cislunar_spacecraft_link_od/main.rs (line 173)

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

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

    let manifest_dir =
        PathBuf::from(std::env::var("CARGO_MANIFEST_DIR").unwrap_or(".".to_string()));

    let out = manifest_dir.join("data/04_output/");

    let almanac = Arc::new(
        Almanac::new(
            &manifest_dir
                .join("data/01_planetary/pck08.pca")
                .to_string_lossy(),
        )
        .unwrap()
        .load(
            &manifest_dir
                .join("data/01_planetary/de440s.bsp")
                .to_string_lossy(),
        )
        .unwrap(),
    );

    let eme2k = almanac.frame_from_uid(EARTH_J2000).unwrap();
    let moon_iau = almanac.frame_from_uid(IAU_MOON_FRAME).unwrap();

    let epoch = Epoch::from_gregorian_tai(2021, 5, 29, 19, 51, 16, 852_000);
    let nrho = Orbit::cartesian(
        166_473.631_302_239_7,
        -274_715.487_253_382_7,
        -211_233.210_176_686_7,
        0.933_451_604_520_018_4,
        0.436_775_046_841_900_9,
        -0.082_211_021_250_348_95,
        epoch,
        eme2k,
    );

    let tx_nrho_sc = Spacecraft::from(nrho);

    let state_luna = almanac.transform_to(nrho, MOON_J2000, None).unwrap();
    println!("Start state (dynamics: Earth, Moon, Sun gravity):\n{state_luna}");

    let bodies = vec![EARTH, SUN];
    let dynamics = SpacecraftDynamics::new(OrbitalDynamics::point_masses(bodies));

    let setup = Propagator::rk89(
        dynamics,
        IntegratorOptions::builder().max_step(0.5.minutes()).build(),
    );

    /* == Propagate the NRHO vehicle == */
    let prop_time = 1.1 * state_luna.period().unwrap();

    let (nrho_final, mut tx_traj) = setup
        .with(tx_nrho_sc, almanac.clone())
        .for_duration_with_traj(prop_time)
        .unwrap();

    tx_traj.name = Some("NRHO Tx SC".to_string());

    println!("{tx_traj}");

    /* == Propagate an LLO vehicle == */
    let llo_orbit =
        Orbit::try_keplerian_altitude(110.0, 1e-4, 90.0, 0.0, 0.0, 0.0, epoch, moon_iau).unwrap();

    let llo_sc = Spacecraft::builder().orbit(llo_orbit).build();

    let (_, llo_traj) = setup
        .with(llo_sc, almanac.clone())
        .until_epoch_with_traj(nrho_final.epoch())
        .unwrap();

    // Export the subset of the first two hours.
    llo_traj
        .clone()
        .filter_by_offset(..2.hours())
        .to_parquet_simple(out.join("05_caps_llo_truth.pq"), almanac.clone())?;

    /* == Setup the interlink == */

    let mut measurement_types = IndexSet::new();
    measurement_types.insert(MeasurementType::Range);
    measurement_types.insert(MeasurementType::Doppler);

    let mut stochastics = IndexMap::new();

    let sa45_csac_allan_dev = 1e-11;

    stochastics.insert(
        MeasurementType::Range,
        StochasticNoise::from_hardware_range_km(
            sa45_csac_allan_dev,
            10.0.seconds(),
            link_specific::ChipRate::StandardT4B,
            link_specific::SN0::Average,
        ),
    );

    stochastics.insert(
        MeasurementType::Doppler,
        StochasticNoise::from_hardware_doppler_km_s(
            sa45_csac_allan_dev,
            10.0.seconds(),
            link_specific::CarrierFreq::SBand,
            link_specific::CN0::Average,
        ),
    );

    let interlink = InterlinkTxSpacecraft {
        traj: tx_traj,
        measurement_types,
        integration_time: None,
        timestamp_noise_s: None,
        ab_corr: Aberration::LT,
        stochastic_noises: Some(stochastics),
    };

    // Devices are the transmitter, which is our NRHO vehicle.
    let mut devices = BTreeMap::new();
    devices.insert("NRHO Tx SC".to_string(), interlink);

    let mut configs = BTreeMap::new();
    configs.insert(
        "NRHO Tx SC".to_string(),
        TrkConfig::builder()
            .strands(vec![Strand {
                start: epoch,
                end: nrho_final.epoch(),
            }])
            .build(),
    );

    let mut trk_sim =
        TrackingArcSim::with_seed(devices.clone(), llo_traj.clone(), configs, 0).unwrap();
    println!("{trk_sim}");

    let trk_data = trk_sim.generate_measurements(almanac.clone()).unwrap();
    println!("{trk_data}");

    trk_data
        .to_parquet_simple(out.clone().join("nrho_interlink_msr.pq"))
        .unwrap();

    // Run a truth OD where we estimate the LLO position
    let llo_uncertainty = SpacecraftUncertainty::builder()
        .nominal(llo_sc)
        .x_km(1.0)
        .y_km(1.0)
        .z_km(1.0)
        .vx_km_s(1e-3)
        .vy_km_s(1e-3)
        .vz_km_s(1e-3)
        .build();

    let mut proc_devices = devices.clone();

    // Define the initial estimate, randomized, seed for reproducibility
    let mut initial_estimate = llo_uncertainty.to_estimate_randomized(Some(0)).unwrap();
    // Inflate the covariance -- https://github.com/nyx-space/nyx/issues/339
    initial_estimate.covar *= 2.5;

    // Increase the noise in the devices to accept more measurements.

    for link in proc_devices.values_mut() {
        for noise in &mut link.stochastic_noises.as_mut().unwrap().values_mut() {
            *noise.white_noise.as_mut().unwrap() *= 3.0;
        }
    }

    let init_err = initial_estimate
        .orbital_state()
        .ric_difference(&llo_orbit)
        .unwrap();

    println!("initial estimate:\n{initial_estimate}");
    println!("RIC errors = {init_err}",);

    let odp = InterlinkKalmanOD::new(
        setup.clone(),
        KalmanVariant::ReferenceUpdate,
        Some(ResidRejectCrit::default()),
        proc_devices,
        almanac.clone(),
    );

    // Shrink the data to process.
    let arc = trk_data.filter_by_offset(..2.hours());

    let od_sol = odp.process_arc(initial_estimate, &arc).unwrap();

    println!("{od_sol}");

    od_sol
        .to_parquet(
            out.join(format!("05_caps_interlink_od_sol.pq")),
            ExportCfg::default(),
        )
        .unwrap();

    let od_traj = od_sol.to_traj().unwrap();

    od_traj
        .ric_diff_to_parquet(
            &llo_traj,
            out.join(format!("05_caps_interlink_llo_est_error.pq")),
            ExportCfg::default(),
        )
        .unwrap();

    let final_est = od_sol.estimates.last().unwrap();
    assert!(final_est.within_3sigma(), "should be within 3 sigma");

    println!("ESTIMATE\n{final_est:x}\n");
    let truth = llo_traj.at(final_est.epoch()).unwrap();
    println!("TRUTH\n{truth:x}");

    let final_err = truth
        .orbit
        .ric_difference(&final_est.orbital_state())
        .unwrap();
    println!("ERROR {final_err}");

    // Build the residuals versus reference plot.
    let rvr_sol = odp
        .process_arc(initial_estimate, &arc.resid_vs_ref_check())
        .unwrap();

    rvr_sol
        .to_parquet(
            out.join(format!("05_caps_interlink_resid_v_ref.pq")),
            ExportCfg::default(),
        )
        .unwrap();

    let final_rvr = rvr_sol.estimates.last().unwrap();

    println!("RMAG error {:.3} m", final_err.rmag_km() * 1e3);
    println!(
        "Pure prop error {:.3} m",
        final_rvr
            .orbital_state()
            .ric_difference(&final_est.orbital_state())
            .unwrap()
            .rmag_km()
            * 1e3
    );

    Ok(())
}

examples/04_lro_od/main.rs (lines 229-234)

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()
        .mass(Mass::from_dry_and_prop_masses(1018.0, 900.0)) // Launch masses
        .srp(SRPData {
            // SRP configuration is arbitrary, but we will be estimating it anyway.
            area_m2: 3.9 * 2.7,
            coeff_reflectivity: 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 24 hours with a five second 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 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_named(ground_station_file)?;

    let mut proc_devices = devices.clone();

    // Increase the noise in the devices to accept more measurements.
    for gs in proc_devices.values_mut() {
        if let Some(noise) = &mut gs
            .stochastic_noises
            .as_mut()
            .unwrap()
            .get_mut(&MeasurementType::Range)
        {
            *noise.white_noise.as_mut().unwrap() *= 3.0;
        }
    }

    // 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, GroundStation>::with_seed(
        devices.clone(),
        traj_as_flown.clone(),
        configs,
        123, // Set a seed for reproducibility
    )?;

    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 mut initial_estimate = sc.to_estimate()?;
    initial_estimate.covar *= 3.0;

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

    // Build the SNC in the Moon J2000 frame, specified as a velocity noise over time.
    let process_noise = ProcessNoise3D::from_velocity_km_s(
        &[1e-10, 1e-10, 1e-10],
        1 * Unit::Hour,
        10 * Unit::Minute,
        None,
    );

    println!("{process_noise}");

    // We'll set up the OD process to reject measurements whose residuals are move than 3 sigmas away from what we expect.
    let odp = SpacecraftKalmanOD::new(
        setup,
        KalmanVariant::ReferenceUpdate,
        Some(ResidRejectCrit::default()),
        proc_devices,
        almanac.clone(),
    )
    .with_process_noise(process_noise);

    let od_sol = odp.process_arc(initial_estimate, &arc)?;

    let final_est = od_sol.estimates.last().unwrap();

    println!("{final_est}");

    let ric_err = traj_as_flown
        .at(final_est.epoch())?
        .orbit
        .ric_difference(&final_est.orbital_state())?;
    println!("== RIC at end ==");
    println!("RIC Position (m): {:.3}", ric_err.radius_km * 1e3);
    println!("RIC Velocity (m/s): {:.3}", ric_err.velocity_km_s * 1e3);

    println!(
        "Num residuals rejected: #{}",
        od_sol.rejected_residuals().len()
    );
    println!(
        "Percentage within +/-3: {}",
        od_sol.residual_ratio_within_threshold(3.0).unwrap()
    );
    println!("Ratios normal? {}", od_sol.is_normal(None).unwrap());

    od_sol.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 = od_sol.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 new( devices: BTreeMap<String, D>, trajectory: Traj<MsrIn>, configs: BTreeMap<String, TrkConfig>, ) -> Result<Self, ConfigError>

Build a new tracking arc simulator using the system entropy to seed the random number generator.

pub fn generate_measurements( &mut self, almanac: Arc<Almanac>, ) -> Result<TrackingDataArc, NyxError>

Generates measurements for the tracking arc using the defined strands

Warning

This function will return an error if any of the devices defines as a scheduler. You must create the schedule first using build_schedule first.

Notes

Although mutable, this function may be called several times to generate different measurements.

Algorithm

For each tracking device, and for each strand within that device, sample the trajectory at the sample rate of the tracking device, adding a measurement whenever the spacecraft is visible. Build the measurements as a vector, ordered chronologically.

Examples found in repository

examples/05_cislunar_spacecraft_link_od/main.rs (line 176)

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

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

    let manifest_dir =
        PathBuf::from(std::env::var("CARGO_MANIFEST_DIR").unwrap_or(".".to_string()));

    let out = manifest_dir.join("data/04_output/");

    let almanac = Arc::new(
        Almanac::new(
            &manifest_dir
                .join("data/01_planetary/pck08.pca")
                .to_string_lossy(),
        )
        .unwrap()
        .load(
            &manifest_dir
                .join("data/01_planetary/de440s.bsp")
                .to_string_lossy(),
        )
        .unwrap(),
    );

    let eme2k = almanac.frame_from_uid(EARTH_J2000).unwrap();
    let moon_iau = almanac.frame_from_uid(IAU_MOON_FRAME).unwrap();

    let epoch = Epoch::from_gregorian_tai(2021, 5, 29, 19, 51, 16, 852_000);
    let nrho = Orbit::cartesian(
        166_473.631_302_239_7,
        -274_715.487_253_382_7,
        -211_233.210_176_686_7,
        0.933_451_604_520_018_4,
        0.436_775_046_841_900_9,
        -0.082_211_021_250_348_95,
        epoch,
        eme2k,
    );

    let tx_nrho_sc = Spacecraft::from(nrho);

    let state_luna = almanac.transform_to(nrho, MOON_J2000, None).unwrap();
    println!("Start state (dynamics: Earth, Moon, Sun gravity):\n{state_luna}");

    let bodies = vec![EARTH, SUN];
    let dynamics = SpacecraftDynamics::new(OrbitalDynamics::point_masses(bodies));

    let setup = Propagator::rk89(
        dynamics,
        IntegratorOptions::builder().max_step(0.5.minutes()).build(),
    );

    /* == Propagate the NRHO vehicle == */
    let prop_time = 1.1 * state_luna.period().unwrap();

    let (nrho_final, mut tx_traj) = setup
        .with(tx_nrho_sc, almanac.clone())
        .for_duration_with_traj(prop_time)
        .unwrap();

    tx_traj.name = Some("NRHO Tx SC".to_string());

    println!("{tx_traj}");

    /* == Propagate an LLO vehicle == */
    let llo_orbit =
        Orbit::try_keplerian_altitude(110.0, 1e-4, 90.0, 0.0, 0.0, 0.0, epoch, moon_iau).unwrap();

    let llo_sc = Spacecraft::builder().orbit(llo_orbit).build();

    let (_, llo_traj) = setup
        .with(llo_sc, almanac.clone())
        .until_epoch_with_traj(nrho_final.epoch())
        .unwrap();

    // Export the subset of the first two hours.
    llo_traj
        .clone()
        .filter_by_offset(..2.hours())
        .to_parquet_simple(out.join("05_caps_llo_truth.pq"), almanac.clone())?;

    /* == Setup the interlink == */

    let mut measurement_types = IndexSet::new();
    measurement_types.insert(MeasurementType::Range);
    measurement_types.insert(MeasurementType::Doppler);

    let mut stochastics = IndexMap::new();

    let sa45_csac_allan_dev = 1e-11;

    stochastics.insert(
        MeasurementType::Range,
        StochasticNoise::from_hardware_range_km(
            sa45_csac_allan_dev,
            10.0.seconds(),
            link_specific::ChipRate::StandardT4B,
            link_specific::SN0::Average,
        ),
    );

    stochastics.insert(
        MeasurementType::Doppler,
        StochasticNoise::from_hardware_doppler_km_s(
            sa45_csac_allan_dev,
            10.0.seconds(),
            link_specific::CarrierFreq::SBand,
            link_specific::CN0::Average,
        ),
    );

    let interlink = InterlinkTxSpacecraft {
        traj: tx_traj,
        measurement_types,
        integration_time: None,
        timestamp_noise_s: None,
        ab_corr: Aberration::LT,
        stochastic_noises: Some(stochastics),
    };

    // Devices are the transmitter, which is our NRHO vehicle.
    let mut devices = BTreeMap::new();
    devices.insert("NRHO Tx SC".to_string(), interlink);

    let mut configs = BTreeMap::new();
    configs.insert(
        "NRHO Tx SC".to_string(),
        TrkConfig::builder()
            .strands(vec![Strand {
                start: epoch,
                end: nrho_final.epoch(),
            }])
            .build(),
    );

    let mut trk_sim =
        TrackingArcSim::with_seed(devices.clone(), llo_traj.clone(), configs, 0).unwrap();
    println!("{trk_sim}");

    let trk_data = trk_sim.generate_measurements(almanac.clone()).unwrap();
    println!("{trk_data}");

    trk_data
        .to_parquet_simple(out.clone().join("nrho_interlink_msr.pq"))
        .unwrap();

    // Run a truth OD where we estimate the LLO position
    let llo_uncertainty = SpacecraftUncertainty::builder()
        .nominal(llo_sc)
        .x_km(1.0)
        .y_km(1.0)
        .z_km(1.0)
        .vx_km_s(1e-3)
        .vy_km_s(1e-3)
        .vz_km_s(1e-3)
        .build();

    let mut proc_devices = devices.clone();

    // Define the initial estimate, randomized, seed for reproducibility
    let mut initial_estimate = llo_uncertainty.to_estimate_randomized(Some(0)).unwrap();
    // Inflate the covariance -- https://github.com/nyx-space/nyx/issues/339
    initial_estimate.covar *= 2.5;

    // Increase the noise in the devices to accept more measurements.

    for link in proc_devices.values_mut() {
        for noise in &mut link.stochastic_noises.as_mut().unwrap().values_mut() {
            *noise.white_noise.as_mut().unwrap() *= 3.0;
        }
    }

    let init_err = initial_estimate
        .orbital_state()
        .ric_difference(&llo_orbit)
        .unwrap();

    println!("initial estimate:\n{initial_estimate}");
    println!("RIC errors = {init_err}",);

    let odp = InterlinkKalmanOD::new(
        setup.clone(),
        KalmanVariant::ReferenceUpdate,
        Some(ResidRejectCrit::default()),
        proc_devices,
        almanac.clone(),
    );

    // Shrink the data to process.
    let arc = trk_data.filter_by_offset(..2.hours());

    let od_sol = odp.process_arc(initial_estimate, &arc).unwrap();

    println!("{od_sol}");

    od_sol
        .to_parquet(
            out.join(format!("05_caps_interlink_od_sol.pq")),
            ExportCfg::default(),
        )
        .unwrap();

    let od_traj = od_sol.to_traj().unwrap();

    od_traj
        .ric_diff_to_parquet(
            &llo_traj,
            out.join(format!("05_caps_interlink_llo_est_error.pq")),
            ExportCfg::default(),
        )
        .unwrap();

    let final_est = od_sol.estimates.last().unwrap();
    assert!(final_est.within_3sigma(), "should be within 3 sigma");

    println!("ESTIMATE\n{final_est:x}\n");
    let truth = llo_traj.at(final_est.epoch()).unwrap();
    println!("TRUTH\n{truth:x}");

    let final_err = truth
        .orbit
        .ric_difference(&final_est.orbital_state())
        .unwrap();
    println!("ERROR {final_err}");

    // Build the residuals versus reference plot.
    let rvr_sol = odp
        .process_arc(initial_estimate, &arc.resid_vs_ref_check())
        .unwrap();

    rvr_sol
        .to_parquet(
            out.join(format!("05_caps_interlink_resid_v_ref.pq")),
            ExportCfg::default(),
        )
        .unwrap();

    let final_rvr = rvr_sol.estimates.last().unwrap();

    println!("RMAG error {:.3} m", final_err.rmag_km() * 1e3);
    println!(
        "Pure prop error {:.3} m",
        final_rvr
            .orbital_state()
            .ric_difference(&final_est.orbital_state())
            .unwrap()
            .rmag_km()
            * 1e3
    );

    Ok(())
}

examples/04_lro_od/main.rs (line 237)

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()
        .mass(Mass::from_dry_and_prop_masses(1018.0, 900.0)) // Launch masses
        .srp(SRPData {
            // SRP configuration is arbitrary, but we will be estimating it anyway.
            area_m2: 3.9 * 2.7,
            coeff_reflectivity: 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 24 hours with a five second 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 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_named(ground_station_file)?;

    let mut proc_devices = devices.clone();

    // Increase the noise in the devices to accept more measurements.
    for gs in proc_devices.values_mut() {
        if let Some(noise) = &mut gs
            .stochastic_noises
            .as_mut()
            .unwrap()
            .get_mut(&MeasurementType::Range)
        {
            *noise.white_noise.as_mut().unwrap() *= 3.0;
        }
    }

    // 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, GroundStation>::with_seed(
        devices.clone(),
        traj_as_flown.clone(),
        configs,
        123, // Set a seed for reproducibility
    )?;

    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 mut initial_estimate = sc.to_estimate()?;
    initial_estimate.covar *= 3.0;

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

    // Build the SNC in the Moon J2000 frame, specified as a velocity noise over time.
    let process_noise = ProcessNoise3D::from_velocity_km_s(
        &[1e-10, 1e-10, 1e-10],
        1 * Unit::Hour,
        10 * Unit::Minute,
        None,
    );

    println!("{process_noise}");

    // We'll set up the OD process to reject measurements whose residuals are move than 3 sigmas away from what we expect.
    let odp = SpacecraftKalmanOD::new(
        setup,
        KalmanVariant::ReferenceUpdate,
        Some(ResidRejectCrit::default()),
        proc_devices,
        almanac.clone(),
    )
    .with_process_noise(process_noise);

    let od_sol = odp.process_arc(initial_estimate, &arc)?;

    let final_est = od_sol.estimates.last().unwrap();

    println!("{final_est}");

    let ric_err = traj_as_flown
        .at(final_est.epoch())?
        .orbit
        .ric_difference(&final_est.orbital_state())?;
    println!("== RIC at end ==");
    println!("RIC Position (m): {:.3}", ric_err.radius_km * 1e3);
    println!("RIC Velocity (m/s): {:.3}", ric_err.velocity_km_s * 1e3);

    println!(
        "Num residuals rejected: #{}",
        od_sol.rejected_residuals().len()
    );
    println!(
        "Percentage within +/-3: {}",
        od_sol.residual_ratio_within_threshold(3.0).unwrap()
    );
    println!("Ratios normal? {}", od_sol.is_normal(None).unwrap());

    od_sol.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 = od_sol.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 TrackingArcSim<Spacecraft, GroundStation>

pub fn generate_schedule( &self, almanac: Arc<Almanac>, ) -> Result<BTreeMap<String, TrkConfig>, NyxError>

Builds the schedule provided the config. Requires the tracker to be a ground station.

Algorithm

1. For each tracking device:
2. Find when the vehicle trajectory has an elevation greater or equal to zero, and use that as the first start of the first tracking arc for this station
3. Find when the vehicle trajectory has an elevation less than zero (i.e. disappears below the horizon), after that initial epoch
4. Repeat 2, 3 until the end of the trajectory
5. Build each of these as “tracking strands” for this tracking device.
6. Organize all of the built tracking strands chronologically.
7. Iterate through all of the strands: 7.a. if that tracker is marked as Greedy and it ends after the start of the next strand, change the start date of the next strand. 7.b. if that tracker is marked as Eager and it ends after the start of the next strand, change the end date of the current strand.

pub fn build_schedule(&mut self, almanac: Arc<Almanac>) -> Result<(), NyxError>

Sets the schedule to that built in build_schedule

Examples found in repository

examples/04_lro_od/main.rs (line 236)

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()
        .mass(Mass::from_dry_and_prop_masses(1018.0, 900.0)) // Launch masses
        .srp(SRPData {
            // SRP configuration is arbitrary, but we will be estimating it anyway.
            area_m2: 3.9 * 2.7,
            coeff_reflectivity: 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 24 hours with a five second 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 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_named(ground_station_file)?;

    let mut proc_devices = devices.clone();

    // Increase the noise in the devices to accept more measurements.
    for gs in proc_devices.values_mut() {
        if let Some(noise) = &mut gs
            .stochastic_noises
            .as_mut()
            .unwrap()
            .get_mut(&MeasurementType::Range)
        {
            *noise.white_noise.as_mut().unwrap() *= 3.0;
        }
    }

    // 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, GroundStation>::with_seed(
        devices.clone(),
        traj_as_flown.clone(),
        configs,
        123, // Set a seed for reproducibility
    )?;

    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 mut initial_estimate = sc.to_estimate()?;
    initial_estimate.covar *= 3.0;

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

    // Build the SNC in the Moon J2000 frame, specified as a velocity noise over time.
    let process_noise = ProcessNoise3D::from_velocity_km_s(
        &[1e-10, 1e-10, 1e-10],
        1 * Unit::Hour,
        10 * Unit::Minute,
        None,
    );

    println!("{process_noise}");

    // We'll set up the OD process to reject measurements whose residuals are move than 3 sigmas away from what we expect.
    let odp = SpacecraftKalmanOD::new(
        setup,
        KalmanVariant::ReferenceUpdate,
        Some(ResidRejectCrit::default()),
        proc_devices,
        almanac.clone(),
    )
    .with_process_noise(process_noise);

    let od_sol = odp.process_arc(initial_estimate, &arc)?;

    let final_est = od_sol.estimates.last().unwrap();

    println!("{final_est}");

    let ric_err = traj_as_flown
        .at(final_est.epoch())?
        .orbit
        .ric_difference(&final_est.orbital_state())?;
    println!("== RIC at end ==");
    println!("RIC Position (m): {:.3}", ric_err.radius_km * 1e3);
    println!("RIC Velocity (m/s): {:.3}", ric_err.velocity_km_s * 1e3);

    println!(
        "Num residuals rejected: #{}",
        od_sol.rejected_residuals().len()
    );
    println!(
        "Percentage within +/-3: {}",
        od_sol.residual_ratio_within_threshold(3.0).unwrap()
    );
    println!("Ratios normal? {}", od_sol.is_normal(None).unwrap());

    od_sol.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 = od_sol.to_traj()?;
    // Build the RIC difference.
    od_trajectory.ric_diff_to_parquet(
        &traj_as_flown,
        "./04_lro_od_truth_error.parquet",
        ExportCfg::default(),
    )?;

    Ok(())
}

Trait Implementations

impl<MsrIn, D> Clone for TrackingArcSim<MsrIn, D>

where D: TrackingDevice<MsrIn> + Clone, MsrIn: State + Interpolatable + Clone, DefaultAllocator: Allocator<<MsrIn as State>::Size> + Allocator<<MsrIn as State>::Size, <MsrIn as State>::Size> + Allocator<<MsrIn as State>::VecLength>,

fn clone(&self) -> TrackingArcSim<MsrIn, D>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<MsrIn, D> Display for TrackingArcSim<MsrIn, D>

where D: TrackingDevice<MsrIn>, MsrIn: Interpolatable, DefaultAllocator: Allocator<<MsrIn as State>::Size> + Allocator<<MsrIn as State>::Size, <MsrIn as State>::Size> + Allocator<<MsrIn as State>::VecLength>,

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

Formats the value using the given formatter.