Struct ProcessNoise 

pub struct ProcessNoise<A: DimName>
where
    DefaultAllocator: Allocator<A> + Allocator<A, A>,
{
    pub start_time: Option<Epoch>,
    pub local_frame: Option<LocalFrame>,
    pub disable_time: Duration,
    pub init_epoch: Option<Epoch>,
    pub prev_epoch: Option<Epoch>,
    /* private fields */
}

Fields

start_time: Option<Epoch>

Time at which this SNC starts to become applicable

local_frame: Option<LocalFrame>

Specify the local frame of this SNC

disable_time: Duration

Enables state noise compensation (process noise) only be applied if the time between measurements is less than the disable_time

init_epoch: Option<Epoch>

prev_epoch: Option<Epoch>

Implementations

impl<A: DimName> ProcessNoise<A>

where DefaultAllocator: Allocator<A> + Allocator<A, A>,

pub fn from_diagonal(disable_time: Duration, values: &[f64]) -> Self

Initialize a state noise compensation structure from the diagonal values

pub fn with_start_time( disable_time: Duration, values: &[f64], start_time: Epoch, ) -> Self

Initialize an SNC with a time at which it should start

pub fn with_decay( disable_time: Duration, initial_snc: &[f64], decay_constants_s: &[f64], ) -> Self

Initialize an exponentially decaying SNC with initial SNC and decay constants. Decay constants in seconds since start of the tracking pass.

pub fn to_matrix(&self, epoch: Epoch) -> Option<OMatrix<f64, A, A>>

Returns the SNC matrix (not incl. Gamma matrix approximation) at the provided Epoch. May be None if:

1. Start time of this matrix is after epoch
2. Time between epoch and previous epoch (set in the Kalman filter!) is longer than disabling time

pub fn propagate<S: DimName>( &self, nominal_orbit: Orbit, delta_t: Duration, ) -> Result<Option<OMatrix<f64, S, S>>, ODError>

where DefaultAllocator: Allocator<S> + Allocator<S, S> + Allocator<S, A> + Allocator<A, S>,

impl ProcessNoise<Const<3>>

pub fn from_velocity_km_s( velocity_noise: &[f64; 3], noise_duration: Duration, disable_time: Duration, local_frame: Option<LocalFrame>, ) -> Self

Initialize the process noise from velocity errors over time

Examples found in repository

nyx-core/examples/06_lunar_orbit_determination/main.rs (lines 189-194)

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",
        "06_lunar_orbit_determination",
    ]
    .iter()
    .collect();

    let meta = data_folder.join("metaalmanac.dhall");

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

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

    // Build a nominal trajectory
    // TODO: Switch this to a sequence once the OD over a spacecraft sequence is implemented.

    let epoch = Epoch::from_gregorian_utc_at_noon(2024, 2, 29);
    let moon_j2000 = almanac.frame_info(MOON_J2000)?;

    // To build the trajectory we need to provide a spacecraft template.
    let orbiter = Spacecraft::builder()
        .mass(Mass::from_dry_and_prop_masses(1018.0, 900.0))
        .srp(SRPData {
            area_m2: 3.9 * 2.7,
            coeff_reflectivity: 0.96,
        })
        .orbit(Orbit::try_keplerian_altitude(
            150.0, 0.00212, 33.6, 45.0, 45.0, 0.0, epoch, moon_j2000,
        )?) // Setting a zero orbit here because it's just a template
        .build();

    // ========================== //
    // === BUILD NOMINAL TRAJ === //
    // ========================== //

    // 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 = GravityField::new(GravityFieldData::from_shadr(
        &jggrx_meta.uri,
        80,
        80,
        true,
        almanac.frame_info(moon_pa_frame)?,
    )?);

    // 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![MOON_J2000], &almanac)?;

    // 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}");

    let setup = Propagator::rk89(dynamics.clone(), IntegratorOptions::default());

    let truth_traj = setup
        .with(orbiter, almanac.clone())
        .for_duration_with_traj(Unit::Day * 2)?
        .1;

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

    // 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 = data_folder.join("dsn-network.yaml");
    let devices = GroundStation::load_named(ground_station_file)?;

    let proc_devices = devices.clone();

    // 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 configs: BTreeMap<String, TrkConfig> =
        TrkConfig::load_named(data_folder.join("tracking-cfg.yaml"))?;

    // Build the tracking arc simulation to generate a "standard measurement".
    let mut trk = TrackingArcSim::<Spacecraft, GroundStation>::with_seed(
        devices.clone(),
        truth_traj.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("./data/04_output/06_lunar_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(orbiter)
        .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{orbiter: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-14, 1e-14, 1e-14],
        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 = SpacecraftKalmanScalarOD::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 = truth_traj
        .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!("Whitened residuals normal? {}", od_sol.is_normal(None)?);
    println!("NIS test success? {}", od_sol.is_nis_consistent(None)?);

    od_sol.to_parquet(
        "./data/04_output/06_lunar_od_results.parquet",
        ExportCfg::default(),
    )?;

    let od_trajectory = od_sol.to_traj()?;
    // Build the RIC difference.
    od_trajectory.ric_diff_to_parquet(
        &truth_traj,
        "./data/04_output/06_lunar_od_truth_error.parquet",
        ExportCfg::default(),
    )?;

    Ok(())
}

nyx-core/examples/04_lro_od/main.rs (lines 279-284)

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 output_folder: PathBuf = [env!("CARGO_MANIFEST_DIR"), "../data", "04_output"]
        .iter()
        .collect();

    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().as_ref())
        .map_err(Box::new)?
        .process(true)
        .map_err(Box::new)?;

    let mut moon_pc = almanac.get_planetary_data_from_id(MOON).unwrap();
    moon_pc.mu_km3_s2 = 4902.74987;
    almanac.set_planetary_data_from_id(MOON, moon_pc).unwrap();

    let mut earth = almanac.get_planetary_data_from_id(EARTH).unwrap();
    earth.mu_km3_s2 = 398600.436;
    almanac.set_planetary_data_from_id(EARTH, earth).unwrap();

    // 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
        .values()
        .next()
        .unwrap()
        .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 = GravityField::new(GravityFieldData::from_shadr(
        &jggrx_meta.uri,
        80,
        80,
        true,
        almanac.frame_info(moon_pa_frame)?,
    )?);

    // 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)?;

    // 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,
        output_folder.join("./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(output_folder.join("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-12, 1e-12, 1e-12],
        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(
        output_folder.join("04_lro_od_results.parquet"),
        ExportCfg::default(),
    )?;

    // Create the ephemeris
    let ephem = od_sol.to_ephemeris("LRO rebuilt".to_string());
    let ephem_start = ephem.start_epoch().unwrap();
    let ephem_end = ephem.end_epoch().unwrap();
    // Check that the covariance is PSD throughout the ephemeris by interpolating it.
    for epoch in TimeSeries::inclusive(ephem_start, ephem_end, Unit::Minute * 5) {
        ephem
            .covar_at(
                epoch,
                anise::ephemerides::ephemeris::LocalFrame::RIC,
                &almanac,
            )
            .unwrap_or_else(|e| panic!("covar not PSD at {epoch}: {e}"));
    }
    // Export as BSP!
    ephem
        .write_spice_bsp(
            -85,
            output_folder.join("04_lro_rebuilt.bsp").to_str().unwrap(),
            None,
        )
        .expect("could not built BSP");
    let new_almanac = Almanac::default()
        .load(output_folder.join("04_lro_rebuilt.bsp").to_str().unwrap())
        .unwrap();
    new_almanac.describe(None, None, None, None, None, None, None, None);
    let (spk_start, spk_end) = new_almanac.spk_domain(-85).unwrap();

    assert!((ephem_start - spk_start).abs() < Unit::Microsecond * 1);
    assert!((ephem_end - spk_end).abs() < Unit::Microsecond * 1);

    // 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,
        output_folder.join("04_lro_od_truth_error.parquet"),
        ExportCfg::default(),
    )?;

    Ok(())
}

Trait Implementations

impl<A: Clone + DimName> Clone for ProcessNoise<A>

where DefaultAllocator: Allocator<A> + Allocator<A, A>,

fn clone(&self) -> ProcessNoise<A>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<A> Debug for ProcessNoise<A>

where A: DimName, DefaultAllocator: Allocator<A> + Allocator<A, A>,

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

Formats the value using the given formatter.

impl<A> Display for ProcessNoise<A>

where A: DimName, DefaultAllocator: Allocator<A> + Allocator<A, A>,

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

Formats the value using the given formatter.