Struct Spacecraft

pub struct Spacecraft {
    pub orbit: Orbit,
    pub dry_mass_kg: f64,
    pub fuel_mass_kg: f64,
    pub srp: SrpConfig,
    pub drag: DragConfig,
    pub thruster: Option<Thruster>,
    pub mode: GuidanceMode,
    pub stm: Option<OMatrix<f64, Const<9>, Const<9>>>,
}

A spacecraft state, composed of its orbit, its dry and fuel (wet) masses (in kg), its SRP configuration, its drag configuration, its thruster configuration, and its guidance mode.

Optionally, the spacecraft state can also store the state transition matrix from the start of the propagation until the current time (i.e. trajectory STM, not step-size STM).

Fields

orbit: Orbit

Initial orbit the vehicle is in

dry_mass_kg: f64

Dry mass, i.e. mass without fuel, in kg

fuel_mass_kg: f64

Fuel mass (if fuel mass is negative, thrusting will fail, unless configured to break laws of physics)

srp: SrpConfig

Solar Radiation Pressure configuration for this spacecraft

drag: DragConfig

thruster: Option<Thruster>

mode: GuidanceMode

Any extra information or extension that is needed for specific guidance laws

stm: Option<OMatrix<f64, Const<9>, Const<9>>>

Optionally stores the state transition matrix from the start of the propagation until the current time (i.e. trajectory STM, not step-size STM) STM is contains position and velocity, Cr, Cd, fuel mass

Implementations

impl Spacecraft

pub fn builder() -> SpacecraftBuilder<((), (), (), (), (), (), (), ())>

Create a builder for building Spacecraft. On the builder, call .orbit(...), .dry_mass_kg(...)(optional), .fuel_mass_kg(...)(optional), .srp(...)(optional), .drag(...)(optional), .thruster(...)(optional), .mode(...)(optional), .stm(...)(optional) to set the values of the fields. Finally, call .build() to create the instance of Spacecraft.

Examples found in repository

examples/03_geo_analysis/stationkeeping.rs (line 39)

fn main() -> Result<(), Box<dyn Error>> {
    pel::init();
    // Set up the dynamics like in the orbit raise.
    let almanac = Arc::new(MetaAlmanac::latest().map_err(Box::new)?);
    let epoch = Epoch::from_gregorian_utc_hms(2024, 2, 29, 12, 13, 14);

    // Define the GEO orbit, and we're just going to maintain it very tightly.
    let earth_j2000 = almanac.frame_from_uid(EARTH_J2000)?;
    let orbit = Orbit::try_keplerian(42164.0, 1e-5, 0., 163.0, 75.0, 0.0, epoch, earth_j2000)?;
    println!("{orbit:x}");

    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();

    // Set up the spacecraft dynamics like in the orbit raise example.

    let prop_time = 30.0 * 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_164.0, 5.0), // 5 km
        Objective::within_tolerance(StateParameter::Eccentricity, 0.001, 5e-5),
        Objective::within_tolerance(StateParameter::Inclination, 0.05, 1e-2),
    ];

    let ruggiero_ctrl = Ruggiero::from_max_eclipse(objectives, sc, 0.2)?;
    println!("{ruggiero_ctrl}");

    let mut orbital_dyn = OrbitalDynamics::point_masses(vec![MOON, SUN]);

    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.
    };
    jgm3_meta.process(true)?;

    let harmonics = Harmonics::from_stor(
        almanac.frame_from_uid(IAU_EARTH_FRAME)?,
        HarmonicsMem::from_cof(&jgm3_meta.uri, 8, 8, true)?,
    );
    orbital_dyn.accel_models.push(harmonics);

    let srp_dyn = SolarPressure::default(EARTH_J2000, almanac.clone())?;
    let sc_dynamics = SpacecraftDynamics::from_model(orbital_dyn, srp_dyn)
        .with_guidance_law(ruggiero_ctrl.clone());

    println!("{sc_dynamics}");

    // Finally, let's use the Monte Carlo framework built into Nyx to propagate spacecraft.

    // Let's start by defining the dispersion.
    // The MultivariateNormal structure allows us to define the dispersions in any of the orbital parameters, but these are applied directly in the Cartesian state space.
    // Note that additional validation on the MVN is in progress -- https://github.com/nyx-space/nyx/issues/339.
    let mc_rv = MvnSpacecraft::new(
        sc,
        vec![StateDispersion::zero_mean(StateParameter::SMA, 3.0)],
    )?;

    let my_mc = MonteCarlo::new(
        sc, // Nominal state
        mc_rv,
        "03_geo_sk".to_string(), // Scenario name
        None, // No specific seed specified, so one will be drawn from the computer's entropy.
    );

    // Build the propagator setup.
    let setup = Propagator::rk89(
        sc_dynamics.clone(),
        IntegratorOptions::builder()
            .min_step(10.0_f64.seconds())
            .error_ctrl(ErrorControl::RSSCartesianStep)
            .build(),
    );

    let num_runs = 25;
    let rslts = my_mc.run_until_epoch(setup, almanac.clone(), sc.epoch() + prop_time, num_runs);

    assert_eq!(rslts.runs.len(), num_runs);

    // For all of the resulting trajectories, we'll want to compute the percentage of penumbra and umbra.

    rslts.to_parquet(
        "03_geo_sk.parquet",
        Some(vec![
            &EclipseLocator::cislunar(almanac.clone()).to_penumbra_event()
        ]),
        ExportCfg::default(),
        almanac,
    )?;

    Ok(())
}

examples/03_geo_analysis/raise.rs (line 52)

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/02_jwst_covar_monte_carlo/main.rs (line 63)

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.
    // For details, refer to https://github.com/nyx-space/anise/blob/master/data/latest.dhall.

    // Download the regularly update of the James Webb Space Telescope reconstucted (or definitive) ephemeris.
    // Refer to https://naif.jpl.nasa.gov/pub/naif/JWST/kernels/spk/aareadme.txt for details.
    let mut latest_jwst_ephem = MetaFile {
        uri: "https://naif.jpl.nasa.gov/pub/naif/JWST/kernels/spk/jwst_rec.bsp".to_string(),
        crc32: None,
    };
    latest_jwst_ephem.process(true)?;

    // Load this ephem in the general Almanac we're using for this analysis.
    let almanac = Arc::new(
        MetaAlmanac::latest()
            .map_err(Box::new)?
            .load_from_metafile(latest_jwst_ephem, true)?,
    );

    // By loading this ephemeris file in the ANISE GUI or ANISE CLI, we can find the NAIF ID of the JWST
    // in the BSP. We need this ID in order to query the ephemeris.
    const JWST_NAIF_ID: i32 = -170;
    // Let's build a frame in the J2000 orientation centered on the JWST.
    const JWST_J2000: Frame = Frame::from_ephem_j2000(JWST_NAIF_ID);

    // Since the ephemeris file is updated regularly, we'll just grab the latest state in the ephem.
    let (earliest_epoch, latest_epoch) = almanac.spk_domain(JWST_NAIF_ID)?;
    println!("JWST defined from {earliest_epoch} to {latest_epoch}");
    // Fetch the state, printing it in the Earth J2000 frame.
    let jwst_orbit = almanac.transform(JWST_J2000, EARTH_J2000, latest_epoch, None)?;
    println!("{jwst_orbit:x}");

    // Build the spacecraft
    // SRP area assumed to be the full sunshield and mass if 6200.0 kg, c.f. https://webb.nasa.gov/content/about/faqs/facts.html
    // SRP Coefficient of reflectivity assumed to be that of Kapton, i.e. 2 - 0.44 = 1.56, table 1 from https://amostech.com/TechnicalPapers/2018/Poster/Bengtson.pdf
    let jwst = Spacecraft::builder()
        .orbit(jwst_orbit)
        .srp(SrpConfig {
            area_m2: 21.197 * 14.162,
            cr: 1.56,
        })
        .dry_mass_kg(6200.0)
        .build();

    // Build up the spacecraft uncertainty builder.
    // We can use the spacecraft uncertainty structure to build this up.
    // We start by specifying the nominal state (as defined above), then the uncertainty in position and velocity
    // in the RIC frame. We could also specify the Cr, Cd, and mass uncertainties, but these aren't accounted for until
    // Nyx can also estimate the deviation of the spacecraft parameters.
    let jwst_uncertainty = SpacecraftUncertainty::builder()
        .nominal(jwst)
        .frame(LocalFrame::RIC)
        .x_km(0.5)
        .y_km(0.3)
        .z_km(1.5)
        .vx_km_s(1e-4)
        .vy_km_s(0.6e-3)
        .vz_km_s(3e-3)
        .build();

    println!("{jwst_uncertainty}");

    // Build the Kalman filter estimate.
    // Note that we could have used the KfEstimate structure directly (as seen throughout the OD integration tests)
    // but this approach requires quite a bit more boilerplate code.
    let jwst_estimate = jwst_uncertainty.to_estimate()?;

    // Set up the spacecraft dynamics.
    // We'll use the point masses of the Earth, Sun, Jupiter (barycenter, because it's in the DE440), and the Moon.
    // We'll also enable solar radiation pressure since the James Webb has a huge and highly reflective sun shield.

    let orbital_dyn = OrbitalDynamics::point_masses(vec![MOON, SUN, JUPITER_BARYCENTER]);
    let srp_dyn = SolarPressure::new(vec![EARTH_J2000, MOON_J2000], almanac.clone())?;

    // Finalize setting up the dynamics.
    let dynamics = SpacecraftDynamics::from_model(orbital_dyn, srp_dyn);

    // Build the propagator set up to use for the whole analysis.
    let setup = Propagator::default(dynamics);

    // All of the analysis will use this duration.
    let prediction_duration = 6.5 * Unit::Day;

    // === Covariance mapping ===
    // For the covariance mapping / prediction, we'll use the common orbit determination approach.
    // This is done by setting up a spacecraft OD process, and predicting for the analysis duration.

    let ckf = KF::no_snc(jwst_estimate);

    // Build the propagation instance for the OD process.
    let prop = setup.with(jwst.with_stm(), almanac.clone());
    let mut odp = SpacecraftODProcess::ckf(prop, ckf, BTreeMap::new(), None, almanac.clone());

    // Define the prediction step, i.e. how often we want to know the covariance.
    let step = 1_i64.minutes();
    // Finally, predict, and export the trajectory with covariance to a parquet file.
    odp.predict_for(step, prediction_duration)?;
    odp.to_parquet(
        &TrackingDataArc::default(),
        "./02_jwst_covar_map.parquet",
        ExportCfg::default(),
    )?;

    // === Monte Carlo framework ===
    // Nyx comes with a complete multi-threaded Monte Carlo frame. It's blazing fast.

    let my_mc = MonteCarlo::new(
        jwst, // Nominal state
        jwst_estimate.to_random_variable()?,
        "02_jwst".to_string(), // Scenario name
        None, // No specific seed specified, so one will be drawn from the computer's entropy.
    );

    let num_runs = 5_000;
    let rslts = my_mc.run_until_epoch(
        setup,
        almanac.clone(),
        jwst.epoch() + prediction_duration,
        num_runs,
    );

    assert_eq!(rslts.runs.len(), num_runs);
    // Finally, export these results, computing the eclipse percentage for all of these results.

    // For all of the resulting trajectories, we'll want to compute the percentage of penumbra and umbra.
    let eclipse_loc = EclipseLocator::cislunar(almanac.clone());
    let umbra_event = eclipse_loc.to_umbra_event();
    let penumbra_event = eclipse_loc.to_penumbra_event();

    rslts.to_parquet(
        "02_jwst_monte_carlo.parquet",
        Some(vec![&umbra_event, &penumbra_event]),
        ExportCfg::default(),
        almanac,
    )?;

    Ok(())
}

examples/03_geo_analysis/drift.rs (line 62)

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/04_lro_od/main.rs (line 79)

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_named(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, GroundStation>::new(
        devices.clone(),
        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 = SpacecraftODProcess::ckf(
        setup.with(initial_estimate.state().with_stm(), almanac.clone()),
        kf,
        devices,
        Some(ResidRejectCrit::default()),
        almanac.clone(),
    );

    odp.process_arc(&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(&arc, "./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(())
}

examples/01_orbit_prop/main.rs (line 92)

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 Spacecraft

pub fn new( orbit: Orbit, dry_mass_kg: f64, fuel_mass_kg: f64, srp_area_m2: f64, drag_area_m2: f64, cr: f64, cd: f64, ) -> Self

Initialize a spacecraft state from all of its parameters

pub fn from_thruster( orbit: Orbit, dry_mass_kg: f64, fuel_mass_kg: f64, thruster: Thruster, mode: GuidanceMode, ) -> Self

Initialize a spacecraft state from only a thruster and mass. Use this when designing guidance laws while ignoring drag and SRP.

pub fn from_srp_defaults( orbit: Orbit, dry_mass_kg: f64, srp_area_m2: f64, ) -> Self

Initialize a spacecraft state from the SRP default 1.8 for coefficient of reflectivity (fuel mass and drag parameters nullified!)

pub fn from_drag_defaults( orbit: Orbit, dry_mass_kg: f64, drag_area_m2: f64, ) -> Self

Initialize a spacecraft state from the SRP default 1.8 for coefficient of drag (fuel mass and SRP parameters nullified!)

pub fn with_dv_km_s(self, dv_km_s: Vector3<f64>) -> Self

pub fn with_dry_mass(self, dry_mass_kg: f64) -> Self

Returns a copy of the state with a new dry mass

pub fn with_fuel_mass(self, fuel_mass_kg: f64) -> Self

Returns a copy of the state with a new fuel mass

pub fn with_srp(self, srp_area_m2: f64, cr: f64) -> Self

Returns a copy of the state with a new SRP area and CR

pub fn with_srp_area(self, srp_area_m2: f64) -> Self

Returns a copy of the state with a new SRP area

pub fn with_cr(self, cr: f64) -> Self

Returns a copy of the state with a new coefficient of reflectivity

pub fn with_drag(self, drag_area_m2: f64, cd: f64) -> Self

Returns a copy of the state with a new drag area and CD

pub fn with_drag_area(self, drag_area_m2: f64) -> Self

Returns a copy of the state with a new SRP area

pub fn with_cd(self, cd: f64) -> Self

Returns a copy of the state with a new coefficient of drag

pub fn with_orbit(self, orbit: Orbit) -> Self

Returns a copy of the state with a new orbit

pub fn rss(&self, other: &Self) -> PhysicsResult<(f64, f64, f64)>

Returns the root sum square error between this spacecraft and the other, in kilometers for the position, kilometers per second in velocity, and kilograms in fuel

pub fn enable_stm(&mut self)

Sets the STM of this state of identity, which also enables computation of the STM for spacecraft navigation

pub fn with_stm(self) -> Self

Copies the current state but sets the STM to identity

Examples found in repository

examples/02_jwst_covar_monte_carlo/main.rs (line 118)

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.
    // For details, refer to https://github.com/nyx-space/anise/blob/master/data/latest.dhall.

    // Download the regularly update of the James Webb Space Telescope reconstucted (or definitive) ephemeris.
    // Refer to https://naif.jpl.nasa.gov/pub/naif/JWST/kernels/spk/aareadme.txt for details.
    let mut latest_jwst_ephem = MetaFile {
        uri: "https://naif.jpl.nasa.gov/pub/naif/JWST/kernels/spk/jwst_rec.bsp".to_string(),
        crc32: None,
    };
    latest_jwst_ephem.process(true)?;

    // Load this ephem in the general Almanac we're using for this analysis.
    let almanac = Arc::new(
        MetaAlmanac::latest()
            .map_err(Box::new)?
            .load_from_metafile(latest_jwst_ephem, true)?,
    );

    // By loading this ephemeris file in the ANISE GUI or ANISE CLI, we can find the NAIF ID of the JWST
    // in the BSP. We need this ID in order to query the ephemeris.
    const JWST_NAIF_ID: i32 = -170;
    // Let's build a frame in the J2000 orientation centered on the JWST.
    const JWST_J2000: Frame = Frame::from_ephem_j2000(JWST_NAIF_ID);

    // Since the ephemeris file is updated regularly, we'll just grab the latest state in the ephem.
    let (earliest_epoch, latest_epoch) = almanac.spk_domain(JWST_NAIF_ID)?;
    println!("JWST defined from {earliest_epoch} to {latest_epoch}");
    // Fetch the state, printing it in the Earth J2000 frame.
    let jwst_orbit = almanac.transform(JWST_J2000, EARTH_J2000, latest_epoch, None)?;
    println!("{jwst_orbit:x}");

    // Build the spacecraft
    // SRP area assumed to be the full sunshield and mass if 6200.0 kg, c.f. https://webb.nasa.gov/content/about/faqs/facts.html
    // SRP Coefficient of reflectivity assumed to be that of Kapton, i.e. 2 - 0.44 = 1.56, table 1 from https://amostech.com/TechnicalPapers/2018/Poster/Bengtson.pdf
    let jwst = Spacecraft::builder()
        .orbit(jwst_orbit)
        .srp(SrpConfig {
            area_m2: 21.197 * 14.162,
            cr: 1.56,
        })
        .dry_mass_kg(6200.0)
        .build();

    // Build up the spacecraft uncertainty builder.
    // We can use the spacecraft uncertainty structure to build this up.
    // We start by specifying the nominal state (as defined above), then the uncertainty in position and velocity
    // in the RIC frame. We could also specify the Cr, Cd, and mass uncertainties, but these aren't accounted for until
    // Nyx can also estimate the deviation of the spacecraft parameters.
    let jwst_uncertainty = SpacecraftUncertainty::builder()
        .nominal(jwst)
        .frame(LocalFrame::RIC)
        .x_km(0.5)
        .y_km(0.3)
        .z_km(1.5)
        .vx_km_s(1e-4)
        .vy_km_s(0.6e-3)
        .vz_km_s(3e-3)
        .build();

    println!("{jwst_uncertainty}");

    // Build the Kalman filter estimate.
    // Note that we could have used the KfEstimate structure directly (as seen throughout the OD integration tests)
    // but this approach requires quite a bit more boilerplate code.
    let jwst_estimate = jwst_uncertainty.to_estimate()?;

    // Set up the spacecraft dynamics.
    // We'll use the point masses of the Earth, Sun, Jupiter (barycenter, because it's in the DE440), and the Moon.
    // We'll also enable solar radiation pressure since the James Webb has a huge and highly reflective sun shield.

    let orbital_dyn = OrbitalDynamics::point_masses(vec![MOON, SUN, JUPITER_BARYCENTER]);
    let srp_dyn = SolarPressure::new(vec![EARTH_J2000, MOON_J2000], almanac.clone())?;

    // Finalize setting up the dynamics.
    let dynamics = SpacecraftDynamics::from_model(orbital_dyn, srp_dyn);

    // Build the propagator set up to use for the whole analysis.
    let setup = Propagator::default(dynamics);

    // All of the analysis will use this duration.
    let prediction_duration = 6.5 * Unit::Day;

    // === Covariance mapping ===
    // For the covariance mapping / prediction, we'll use the common orbit determination approach.
    // This is done by setting up a spacecraft OD process, and predicting for the analysis duration.

    let ckf = KF::no_snc(jwst_estimate);

    // Build the propagation instance for the OD process.
    let prop = setup.with(jwst.with_stm(), almanac.clone());
    let mut odp = SpacecraftODProcess::ckf(prop, ckf, BTreeMap::new(), None, almanac.clone());

    // Define the prediction step, i.e. how often we want to know the covariance.
    let step = 1_i64.minutes();
    // Finally, predict, and export the trajectory with covariance to a parquet file.
    odp.predict_for(step, prediction_duration)?;
    odp.to_parquet(
        &TrackingDataArc::default(),
        "./02_jwst_covar_map.parquet",
        ExportCfg::default(),
    )?;

    // === Monte Carlo framework ===
    // Nyx comes with a complete multi-threaded Monte Carlo frame. It's blazing fast.

    let my_mc = MonteCarlo::new(
        jwst, // Nominal state
        jwst_estimate.to_random_variable()?,
        "02_jwst".to_string(), // Scenario name
        None, // No specific seed specified, so one will be drawn from the computer's entropy.
    );

    let num_runs = 5_000;
    let rslts = my_mc.run_until_epoch(
        setup,
        almanac.clone(),
        jwst.epoch() + prediction_duration,
        num_runs,
    );

    assert_eq!(rslts.runs.len(), num_runs);
    // Finally, export these results, computing the eclipse percentage for all of these results.

    // For all of the resulting trajectories, we'll want to compute the percentage of penumbra and umbra.
    let eclipse_loc = EclipseLocator::cislunar(almanac.clone());
    let umbra_event = eclipse_loc.to_umbra_event();
    let penumbra_event = eclipse_loc.to_penumbra_event();

    rslts.to_parquet(
        "02_jwst_monte_carlo.parquet",
        Some(vec![&umbra_event, &penumbra_event]),
        ExportCfg::default(),
        almanac,
    )?;

    Ok(())
}

examples/04_lro_od/main.rs (line 261)

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_named(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, GroundStation>::new(
        devices.clone(),
        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 = SpacecraftODProcess::ckf(
        setup.with(initial_estimate.state().with_stm(), almanac.clone()),
        kf,
        devices,
        Some(ResidRejectCrit::default()),
        almanac.clone(),
    );

    odp.process_arc(&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(&arc, "./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 mass_kg(&self) -> f64

Returns the total mass in kilograms

pub fn with_guidance_mode(self, mode: GuidanceMode) -> Self

Returns a copy of the state with the provided guidance mode

pub fn mode(&self) -> GuidanceMode

pub fn mut_mode(&mut self, mode: GuidanceMode)

Trait Implementations

impl Add<Matrix<f64, Const<6>, Const<1>, <DefaultAllocator as Allocator<Const<6>>>::Buffer<f64>>> for Spacecraft

fn add(self, other: OVector<f64, Const<6>>) -> Self

Adds the provided state deviation to this orbit

type Output = Spacecraft

The resulting type after applying the + operator.

impl Add<Matrix<f64, Const<9>, Const<1>, <DefaultAllocator as Allocator<Const<9>>>::Buffer<f64>>> for Spacecraft

fn add(self, other: OVector<f64, Const<9>>) -> Self

Adds the provided state deviation to this orbit

type Output = Spacecraft

The resulting type after applying the + operator.

impl Clone for Spacecraft

fn clone(&self) -> Spacecraft

Returns a copy of the value.

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

Performs copy-assignment from source.

impl ConfigRepr for Spacecraft

fn load<P>(path: P) -> Result<Self, ConfigError>

where P: AsRef<Path>,

Builds the configuration representation from the path to a yaml

fn load_many<P>(path: P) -> Result<Vec<Self>, ConfigError>

where P: AsRef<Path>,

Builds a sequence of “Selves” from the provided path to a yaml

fn load_named<P>(path: P) -> Result<BTreeMap<String, Self>, ConfigError>

where P: AsRef<Path>,

Builds a map of names to “selves” from the provided path to a yaml

fn loads_many(data: &str) -> Result<Vec<Self>, ConfigError>

Builds a sequence of “Selves” from the provided string of a yaml

fn loads_named(data: &str) -> Result<BTreeMap<String, Self>, ConfigError>

Builds a sequence of “Selves” from the provided string of a yaml

impl Debug for Spacecraft

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

Formats the value using the given formatter.

impl Default for Spacecraft

fn default() -> Self

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for Spacecraft

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Display for Spacecraft

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

Formats the value using the given formatter.

impl EventEvaluator<Spacecraft> for Event

fn eval( &self, state: &Spacecraft, almanac: Arc<Almanac>, ) -> Result<f64, EventError>

Evaluation of the event, must return a value corresponding to whether the state is before or after the event

fn epoch_precision(&self) -> Duration

fn value_precision(&self) -> f64

fn eval_string( &self, state: &Spacecraft, _almanac: Arc<Almanac>, ) -> Result<String, EventError>

Returns a string representation of the event evaluation for the given state

fn eval_crossing( &self, prev_state: &S, next_state: &S, almanac: Arc<Almanac>, ) -> Result<bool, EventError>

impl EventEvaluator<Spacecraft> for PenumbraEvent

fn epoch_precision(&self) -> Duration

Stop searching when the time has converged to less than 0.1 seconds

fn value_precision(&self) -> f64

Finds the slightest penumbra within 2% (i.e. 98% in visibility)

fn eval( &self, sc: &Spacecraft, almanac: Arc<Almanac>, ) -> Result<f64, EventError>

Evaluation of the event, must return a value corresponding to whether the state is before or after the event

fn eval_string( &self, state: &Spacecraft, almanac: Arc<Almanac>, ) -> Result<String, EventError>

Returns a string representation of the event evaluation for the given state

fn eval_crossing( &self, prev_state: &S, next_state: &S, almanac: Arc<Almanac>, ) -> Result<bool, EventError>

impl EventEvaluator<Spacecraft> for UmbraEvent

fn epoch_precision(&self) -> Duration

Stop searching when the time has converged to less than 0.1 seconds

fn value_precision(&self) -> f64

Finds the darkest part of an eclipse within 2% of penumbra (i.e. 98% in shadow)

fn eval( &self, sc: &Spacecraft, almanac: Arc<Almanac>, ) -> Result<f64, EventError>

Evaluation of the event, must return a value corresponding to whether the state is before or after the event

fn eval_string( &self, state: &Spacecraft, almanac: Arc<Almanac>, ) -> Result<String, EventError>

Returns a string representation of the event evaluation for the given state

fn eval_crossing( &self, prev_state: &S, next_state: &S, almanac: Arc<Almanac>, ) -> Result<bool, EventError>

impl From<CartesianState> for Spacecraft

fn from(orbit: Orbit) -> Self

Converts to this type from the input type.

impl Interpolatable for Spacecraft

fn interpolate( self, epoch: Epoch, states: &[Self], ) -> Result<Self, InterpolationError>

Interpolates a new state at the provided epochs given a slice of states.

fn frame(&self) -> Frame

Returns the frame of this state

fn set_frame(&mut self, frame: Frame)

Sets the frame of this state

fn export_params() -> Vec<StateParameter>

List of state parameters that will be exported to a trajectory file in addition to the epoch (provided in this different formats).

impl LowerExp for Spacecraft

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

Formats the value using the given formatter.

impl LowerHex for Spacecraft

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

Formats the value using the given formatter.

impl NavSolution<Spacecraft> for KfEstimate<Spacecraft>

fn orbital_state(&self) -> Orbit

fn expected_state(&self) -> Orbit

Returns the nominal state as computed by the dynamics

impl PartialEq for Spacecraft

fn eq(&self, other: &Self) -> 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 Serialize for Spacecraft

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl State for Spacecraft

fn to_vector(&self) -> OVector<f64, Const<90>>

The vector is organized as such: [X, Y, Z, Vx, Vy, Vz, Cr, Cd, Fuel mass, STM(9x9)]

fn set(&mut self, epoch: Epoch, vector: &OVector<f64, Const<90>>)

Vector is expected to be organized as such: [X, Y, Z, Vx, Vy, Vz, Cr, Cd, Fuel mass, STM(9x9)]

fn stm(&self) -> Result<OMatrix<f64, Self::Size, Self::Size>, DynamicsError>

diag(STM) = [X,Y,Z,Vx,Vy,Vz,Cr,Cd,Fuel] WARNING: Currently the STM assumes that the fuel mass is constant at ALL TIMES!

type Size = Const<9>

Size of the state and its STM

type VecLength = Const<90>

fn reset_stm(&mut self)

Return this state as a vector for the propagation/estimation By default, this is not implemented. This function must be implemented when filtering on this state.

fn zeros() -> Self

Initialize an empty state By default, this is not implemented. This function must be implemented when filtering on this state.

fn epoch(&self) -> Epoch

Retrieve the Epoch

fn set_epoch(&mut self, epoch: Epoch)

Set the Epoch

fn add(self, other: OVector<f64, Self::Size>) -> Self

By default, this is not implemented. This function must be implemented when filtering on this state.

fn value(&self, param: StateParameter) -> Result<f64, StateError>

Return the value of the parameter, returns an error by default

fn set_value( &mut self, param: StateParameter, val: f64, ) -> Result<(), StateError>

Allows setting the value of the given parameter. NOTE: Most parameters where the value is available CANNOT be also set for that parameter (it’s a much harder problem!)

fn unset_stm(&mut self)

Unsets the STM for this state

fn orbit(&self) -> Orbit

Returns a copy of the orbit

fn set_orbit(&mut self, orbit: Orbit)

Modifies this state’s orbit

fn set_with_delta_seconds( self, delta_t_s: f64, vector: &OVector<f64, Self::VecLength>, ) -> Self

where DefaultAllocator: Allocator<Self::VecLength>,

Reconstruct a new State from the provided delta time in seconds compared to the current state and with the provided vector.

impl TrackerSensitivity<Spacecraft, Spacecraft> for GroundStation

where DefaultAllocator: Allocator<<Spacecraft as State>::Size> + Allocator<<Spacecraft as State>::VecLength> + Allocator<<Spacecraft as State>::Size, <Spacecraft as State>::Size>,

fn h_tilde<M: DimName>( &self, msr: &Measurement, msr_types: &IndexSet<MeasurementType>, rx: &Spacecraft, almanac: Arc<Almanac>, ) -> Result<OMatrix<f64, M, <Spacecraft as State>::Size>, ODError>

where DefaultAllocator: Allocator<M> + Allocator<M, <Spacecraft as State>::Size>,

Returns the sensitivity matrix of size MxS where M is the number of simultaneous measurements and S is the size of the state being solved for.

impl TrackingDevice<Spacecraft> for GroundStation

fn measure( &mut self, epoch: Epoch, traj: &Traj<Spacecraft>, rng: Option<&mut Pcg64Mcg>, almanac: Arc<Almanac>, ) -> Result<Option<Measurement>, ODError>

Perform a measurement from the ground station to the receiver (rx).

fn measurement_covar( &self, msr_type: MeasurementType, epoch: Epoch, ) -> Result<f64, ODError>

Returns the measurement noise of this ground station.

Methodology

Noises are modeled using a [StochasticNoise] process, defined by the sigma on the turn-on bias and on the steady state noise. The measurement noise is computed assuming that all measurements are independent variables, i.e. the measurement matrix is a diagonal matrix. The first item in the diagonal is the range noise (in km), set to the square of the steady state sigma. The second item is the Doppler noise (in km/s), set to the square of the steady state sigma of that Gauss Markov process.

fn measurement_types(&self) -> &IndexSet<MeasurementType>

Returns the enabled measurement types for thie device.

fn name(&self) -> String

Returns the name of this tracking data simulator

fn location( &self, epoch: Epoch, frame: Frame, almanac: Arc<Almanac>, ) -> AlmanacResult<Orbit>

Returns the device location at the given epoch and in the given frame.

fn measure_instantaneous( &mut self, rx: Spacecraft, rng: Option<&mut Pcg64Mcg>, almanac: Arc<Almanac>, ) -> Result<Option<Measurement>, ODError>

fn measurement_covar_matrix<M: DimName>( &self, msr_types: &IndexSet<MeasurementType>, epoch: Epoch, ) -> Result<OMatrix<f64, M, M>, ODError>

where DefaultAllocator: Allocator<M, M>,

impl UpperHex for Spacecraft

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

Formats the value using the given formatter.

impl Copy for Spacecraft