Struct GroundStation 

pub struct GroundStation {
    pub name: String,
    pub location: Location,
    pub measurement_types: IndexSet<MeasurementType>,
    pub integration_time: Option<Duration>,
    pub light_time_correction: bool,
    pub timestamp_noise_s: Option<StochasticNoise>,
    pub stochastic_noises: Option<IndexMap<MeasurementType, StochasticNoise>>,
}

GroundStation defines a one-way or two-way ranging and doppler station. Set the integration time for two-way.

Fields

name: String

location: Location

measurement_types: IndexSet<MeasurementType>

integration_time: Option<Duration>

Duration needed to generate a measurement (if unset, it is assumed to be instantaneous)

light_time_correction: bool

Whether to correct for light travel time

timestamp_noise_s: Option<StochasticNoise>

Noise on the timestamp of the measurement

stochastic_noises: Option<IndexMap<MeasurementType, StochasticNoise>>

Implementations

impl GroundStation

pub fn dss65_madrid( elevation_mask_deg: f64, range_noise_km: StochasticNoise, doppler_noise_km_s: StochasticNoise, ) -> Self

pub fn dss34_canberra( elevation_mask_deg: f64, range_noise_km: StochasticNoise, doppler_noise_km_s: StochasticNoise, ) -> Self

pub fn dss13_goldstone( elevation_mask_deg: f64, range_noise_km: StochasticNoise, doppler_noise_km_s: StochasticNoise, ) -> Self

impl GroundStation

pub fn azimuth_elevation_of( &self, rx: Orbit, obstructing_body: Option<Frame>, almanac: &Almanac, ) -> AlmanacResult<AzElRange>

Computes the azimuth and elevation of the provided object seen from this ground station, both in degrees. This is a shortcut to almanac.azimuth_elevation_range_sez.

pub fn to_orbit(&self, epoch: Epoch, almanac: &Almanac) -> AlmanacResult<Orbit>

Return this ground station as an orbit in its current frame

Examples found in repository

nyx-core/examples/01_orbit_prop/main.rs (line 250)

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_info(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)
        .mass(Mass::from_dry_mass(9.60))
        .srp(SRPData {
            area_m2: 10e-4,
            coeff_reflectivity: 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 = GravityField::new(
        GravityFieldData::from_cof(
            &jgm3_meta.uri,
            21,
            21,
            true,
            almanac.frame_info(IAU_EARTH_FRAME)?,
        )
        .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_flux(EARTH_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}");

    // 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",
        "CUBESAT-ID".to_string(),
        Some("Nyx Space".to_string()),
        Some("CUBESAT".to_string()),
        ExportCfg::builder().step(Unit::Minute * 2).build(),
    )?;

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

    // 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_info(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(&Column::Scalar(ScalarColumn::new(
            "elevation mask (deg)".into(),
            Scalar::new(DataType::Float64, AnyValue::Float64(15.0)),
            offset_s.len(),
        )))?;
    let cubesat_visible = aer_df.filter(&mask)?;

    println!("{cubesat_visible}");

    Ok(())
}

impl GroundStation

pub fn from_point( name: String, latitude_deg: f64, longitude_deg: f64, height_km: f64, frame: Frame, ) -> Self

Initializes a point on the surface of a celestial object. This is meant for analysis, not for spacecraft navigation.

Examples found in repository

nyx-core/examples/01_orbit_prop/main.rs (lines 205-211)

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_info(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)
        .mass(Mass::from_dry_mass(9.60))
        .srp(SRPData {
            area_m2: 10e-4,
            coeff_reflectivity: 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 = GravityField::new(
        GravityFieldData::from_cof(
            &jgm3_meta.uri,
            21,
            21,
            true,
            almanac.frame_info(IAU_EARTH_FRAME)?,
        )
        .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_flux(EARTH_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}");

    // 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",
        "CUBESAT-ID".to_string(),
        Some("Nyx Space".to_string()),
        Some("CUBESAT".to_string()),
        ExportCfg::builder().step(Unit::Minute * 2).build(),
    )?;

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

    // 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_info(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(&Column::Scalar(ScalarColumn::new(
            "elevation mask (deg)".into(),
            Scalar::new(DataType::Float64, AnyValue::Float64(15.0)),
            offset_s.len(),
        )))?;
    let cubesat_visible = aer_df.filter(&mask)?;

    println!("{cubesat_visible}");

    Ok(())
}

pub fn with_msr_type( self, msr_type: MeasurementType, noise: StochasticNoise, ) -> Self

Returns a copy of this ground station with the new measurement type added (or replaced)

pub fn without_msr_type(self, msr_type: MeasurementType) -> Self

Returns a copy of this ground station without the provided measurement type (if defined, else no error)

pub fn with_integration_time(self, integration_time: Option<Duration>) -> Self

pub fn with_msr_bias_constant( self, msr_type: MeasurementType, bias_constant: f64, ) -> Result<Self, ODError>

Returns a copy of this ground station with the measurement type noises’ constant bias set to the provided value.

impl GroundStation

pub fn from_asn1(_cls: &Bound<'_, PyType>, data: &[u8]) -> PyResult<Self>

Decodes an ASN.1 DER encoded byte array into a GroundStation object.

:type data: bytes :rtype: GroundStation

pub fn to_asn1<'py>(&self, py: Python<'py>) -> PyResult<Bound<'py, PyBytes>>

Encodes this GroundStation object into an ASN.1 DER encoded byte array.

:rtype: bytes

Trait Implementations

impl Clone for GroundStation

fn clone(&self) -> GroundStation

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl ConfigRepr for GroundStation

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 GroundStation

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

Formats the value using the given formatter.

impl<'a> Decode<'a> for GroundStation

fn decode<R: Reader<'a>>(decoder: &mut R) -> Result<Self>

Attempt to decode this message using the provided decoder.

fn from_der(bytes: &'a [u8]) -> Result<Self, Error>

Parse Self from the provided DER-encoded byte slice.

impl Default for GroundStation

fn default() -> Self

Returns the “default value” for a type.

impl DerefToPyAny for GroundStation

impl<'de> Deserialize<'de> for GroundStation

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

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Display for GroundStation

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

Formats the value using the given formatter.

impl Encode for GroundStation

fn encoded_len(&self) -> Result<Length>

Compute the length of this value in bytes when encoded as ASN.1 DER.

fn encode(&self, encoder: &mut impl Writer) -> Result<()>

Encode this value as ASN.1 DER using the provided [Writer].

fn encode_to_slice<'a>(&self, buf: &'a mut [u8]) -> Result<&'a [u8], Error>

Encode this value to the provided byte slice, returning a sub-slice containing the encoded message.

fn encode_to_vec(&self, buf: &mut Vec<u8>) -> Result<Length, Error>

Encode this message as ASN.1 DER, appending it to the provided byte vector.

fn to_der(&self) -> Result<Vec<u8>, Error>

Encode this type as DER, returning a byte vector.

impl<'a, 'py> FromPyObject<'a, 'py> for GroundStation

where Self: Clone,

type Error = PyClassGuardError<'a, 'py>

The type returned in the event of a conversion error.

fn extract( obj: Borrowed<'a, 'py, PyAny>, ) -> Result<Self, <Self as FromPyObject<'a, 'py>>::Error>

Extracts Self from the bound smart pointer obj.

impl<'py> IntoPyObject<'py> for GroundStation

type Target = GroundStation

The Python output type

type Output = Bound<'py, <GroundStation as IntoPyObject<'py>>::Target>

The smart pointer type to use.

type Error = PyErr

The type returned in the event of a conversion error.

fn into_pyobject( self, py: Python<'py>, ) -> Result<<Self as IntoPyObject<'_>>::Output, <Self as IntoPyObject<'_>>::Error>

Performs the conversion.

impl PartialEq for GroundStation

fn eq(&self, other: &GroundStation) -> 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 PyClass for GroundStation

const NAME: &str = "GroundStation"

Name of the class.

type Frozen = False

Whether the pyclass is frozen.

impl PyClassImpl for GroundStation

const MODULE: Option<&str> = ::core::option::Option::None

Module which the class will be associated with.

const IS_BASETYPE: bool = false

#[pyclass(subclass)]

const IS_SUBCLASS: bool = false

#[pyclass(extends=…)]

const IS_MAPPING: bool = false

#[pyclass(mapping)]

const IS_SEQUENCE: bool = false

#[pyclass(sequence)]

const IS_IMMUTABLE_TYPE: bool = false

#[pyclass(immutable_type)]

const RAW_DOC: &'static CStr = /// GroundStation defines a one-way or two-way ranging and doppler station. Set the integration time for two-way.

Docstring for the class provided on the struct or enum.

const DOC: &'static CStr

Fully rendered class doc, including the text_signature if a constructor is defined.

type Layout = <<GroundStation as PyClassImpl>::BaseNativeType as PyClassBaseType>::Layout<GroundStation>

Description of how this class is laid out in memory

type BaseType = PyAny

Base class

type ThreadChecker = NoopThreadChecker

This handles following two situations:

type Inventory = Pyo3MethodsInventoryForGroundStation

type PyClassMutability = <<PyAny as PyClassBaseType>::PyClassMutability as PyClassMutability>::MutableChild

Immutable or mutable

type Dict = PyClassDummySlot

Specify this class has #[pyclass(dict)] or not.

type WeakRef = PyClassDummySlot

Specify this class has #[pyclass(weakref)] or not.

type BaseNativeType = PyAny

The closest native ancestor. This is PyAny by default, and when you declare #[pyclass(extends=PyDict)], it’s PyDict.

fn items_iter() -> PyClassItemsIter

fn lazy_type_object() -> &'static LazyTypeObject<Self>

fn dict_offset() -> Option<PyObjectOffset>

Used to provide the dictoffset slot (equivalent to tp_dictoffset)

fn weaklist_offset() -> Option<PyObjectOffset>

Used to provide the weaklistoffset slot (equivalent to tp_weaklistoffset

impl PyClassNewTextSignature for GroundStation

const TEXT_SIGNATURE: &'static str = "(name, location, stochastic_noises, integration_time=None, light_time_correction=False, timestamp_noise_s=None)"

impl PyClass__eq__SlotFragment<GroundStation> for PyClassImplCollector<GroundStation>

unsafe fn __eq__( self, py: Python<'_>, _slf: *mut PyObject, arg0: *mut PyObject, ) -> PyResult<*mut PyObject>

Safety: _slf and _other must be valid non-null Python objects

impl PyTypeInfo for GroundStation

const NAME: &str = <Self as ::pyo3::PyClass>::NAME

👎Deprecated since 0.28.0:

prefer using ::type_object(py).name() to get the correct runtime value

Class name.

const MODULE: Option<&str> = <Self as ::pyo3::impl_::pyclass::PyClassImpl>::MODULE

👎Deprecated since 0.28.0:

prefer using ::type_object(py).module() to get the correct runtime value

Module name, if any.

fn type_object_raw(py: Python<'_>) -> *mut PyTypeObject

Returns the PyTypeObject instance for this type.

fn type_object(py: Python<'_>) -> Bound<'_, PyType>

Returns the safe abstraction over the type object.

fn is_type_of(object: &Bound<'_, PyAny>) -> bool

Checks if object is an instance of this type or a subclass of this type.

fn is_exact_type_of(object: &Bound<'_, PyAny>) -> bool

Checks if object is an instance of this type.

impl ScalarSensitivityT<Spacecraft, Spacecraft, GroundStation> for ScalarSensitivity<Spacecraft, Spacecraft, GroundStation>

fn new( msr_type: MeasurementType, msr: &Measurement, rx: &Spacecraft, tx: &GroundStation, almanac: Arc<Almanac>, ) -> Result<Self, ODError>

impl Serialize for GroundStation

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

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for GroundStation

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_bias( &self, msr_type: MeasurementType, _epoch: Epoch, ) -> Result<f64, 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>,

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

where DefaultAllocator: Allocator<M>,