2. DiffOneWayRangeIdeal#

class DiffOneWayRangeIdeal(name: str, instrument: Instrument, sigma: ArrayWUnits = None, gs_range_bias: float = None, state_definition: StateArray = None, sequence_definition=None, ground_station_2: GroundStation = None)#

Bases: Measurement

Models the ideal differential one-way ranging measurement model.

Generates differenced ranging observables between an two observers and a target. The differenced ranging observables are expressed in sec

Parameters:

  • name (str) – name of the measurement model

  • instrument (Instrument) – instrument object associated with the measurement model

  • sigma (ArrayWUnits, optional) – Measurement standard deviation in seconds. Defaults to None.

  • gs_range_bias (float, optional) – Measurement bias. Defaults to None.

  • state_definition (StateVector, optional) – State vector definition list. Defaults to None.

  • sequence_definition (list, optional) – sequence definition list. Optional, defaults to None.

  • ground_station_2 (GroundStation, optional) – Second ground station needed for measurement model (differential). Defaults to None.

Attributes

gs_number

The ground station number

gs_range_bias

DESC

instrument

The instrument.

name

The name of the model.

sequence_definition

The sequence definition.

sigma

The standard deviation of the measurement model.

state_definition

The state vector definition

station

The station of the measurement model.

Methods

compute_h_tilde_dv_man()

Generates the portion in the h_tilde matrix relative to the partial of the ideal DOR measurement model with respect to the maneuver DV components.

compute_h_tilde_eta_srp()

Generates the portion in the h_tilde matrix relative to the partial of the ideal DOR measurement model with respect to the srp scaling factor (eta_srp).

compute_h_tilde_gs_location(...)

Generates the portion in the h_tilde matrix relative to the partial of the ideal range measurement model with respect to the ground station position components.

compute_h_tilde_pos(relative_state_1, ...)

Generates the portion in the h_tilde matrix relative to the partial of the ideal DOR measurement model with respect to the position components.

compute_h_tilde_range_bias()

Generates the portion in the h_tilde matrix relative to the partial of the ideal DOR measurement model with respect to the range bias.

compute_h_tilde_vel()

Generates the portion in the h_tilde matrix relative to the partial of the DOR measurement model with respect to the velocity components.

compute_partials(target, epoch_array[, frame])

Stacks together measurement partials for an epoch array at different epochs.

computed_measurements(target[, epoch_array, ...])

Computes the doppler measurement between target.name and self.instrument.name (2-way doppler).

generate_measurement_dataset(dataset_name, ...)

Generates a MeasurementDataSet object that can be used by filters downstream.

observed_measurements(file_name[, ...])

Reads measurements from a .json file.

partials(target, epoch, frame)

Groups toghether the different components of measurement partials in the global H-tilde.

residuals(observed_meas, computed_meas)

Generates the measurement model's residuals given observed and computed ArrayWFrames.

write_observed_measurements(target[, ...])

Generates synthetic measurements and write them as a .json file.
compute_h_tilde_dv_man() → ndarray#

Generates the portion in the h_tilde matrix relative to the partial of the ideal DOR measurement model with respect to the maneuver DV components.

Returns:

partials – The 3x1 partial derivatives of the measurement model by the maneuver DV components

Return type:

numpy.ndarray

References

“Statistical Orbit Determination”, B. D. Tapley, B. E. Schutz, and G. H. Born, 2004 (pg. 161, eq. 4.2.6)

compute_h_tilde_eta_srp() → ndarray#

Generates the portion in the h_tilde matrix relative to the partial of the ideal DOR measurement model with respect to the srp scaling factor (eta_srp).

Returns:

partial – The scalar partial derivative of the measurement model by the position components

Return type:

numpy.ndarray

References

“Statistical Orbit Determination”, B. D. Tapley, B. E. Schutz, and G. H. Born, 2004 (pg. 161, eq. 4.2.6)

compute_h_tilde_gs_location(relative_state_1: ArrayWUnits, relative_state_2: ArrayWUnits) → ndarray#

Generates the portion in the h_tilde matrix relative to the partial of the ideal range measurement model with respect to the ground station position components.

Parameters:

  • relative_state_1 (ArrayWUnits) – The relative state between ground station #1 and the target,

  • relative_state_2 (ArrayWUnits) – The relative state between ground station #2 and the target.

Returns:

partials – The 3x1partial derivatives of the measurement model by the position components.

Return type:

numpy.ndarray

References

“Statistical Orbit Determination”, B. D. Tapley, B. E. Schutz, and G. H. Born, 2004 (pg. 161, eq. 4.2.6)

compute_h_tilde_pos(relative_state_1: ArrayWUnits, relative_state_2: ArrayWUnits) → ndarray#

Generates the portion in the h_tilde matrix relative to the partial of the ideal DOR measurement model with respect to the position components.

Parameters:

  • relative_state_1 (ArrayWUnits) – The relative state between ground station #1 and the target.

  • relative_state_2 (ArrayWYnts) – The relative state between ground station #2 and the target.

Returns:

partials – The 3x1 partial derivatives of the measurement model by the position components

Return type:

numpy.ndarray

References

“Statistical Orbit Determination”, B. D. Tapley, B. E. Schutz, and G. H. Born, 2004 (pg. 161, eq. 4.2.6)

compute_h_tilde_range_bias() → ndarray#

Generates the portion in the h_tilde matrix relative to the partial of the ideal DOR measurement model with respect to the range bias.

Returns:

partial – The scalar partial derivative of the measurement model by the position components.

Return type:

numpy.ndarray

References

“Statistical Orbit Determination”, B. D. Tapley, B. E. Schutz, and G. H. Born, 2004 (pg. 161, eq. 4.2.6)

compute_h_tilde_vel() → ndarray#

Generates the portion in the h_tilde matrix relative to the partial of the DOR measurement model with respect to the velocity components.

Returns:

partials – The 3x1 partial derivatives of the measurement model by the velocity components

Return type:

numpy.ndarray

References

“Statistical Orbit Determination”, B. D. Tapley, B. E. Schutz, and G. H. Born, 2004 (pg. 161, eq. 4.2.6)

compute_partials(target: ~scarabaeus.spacecraft.Spacecraft.Spacecraft, epoch_array: ~scarabaeus.timeAndFrame.EpochArray.EpochArray, frame: ~scarabaeus.timeAndFrame.Frame.Frame = J2000 (0 - SOLAR SYSTEM BARYCENTER)) → list#

Stacks together measurement partials for an epoch array at different epochs.

Parameters:

  • target (Spacecraft) – The target spacecraft.

  • epoch_array (EpochArray) – The epochs.

  • frame (Frame, optional) – The reference frame. Defaults to a J2000 Frame object.

Returns:

partials – A list with all the partials evaluated at different epochs in the epoch_array.

Return type:

list

computed_measurements(target: ~scarabaeus.spacecraft.Spacecraft.Spacecraft, epoch_array: ~scarabaeus.timeAndFrame.EpochArray.EpochArray = None, epoch_start: ~scarabaeus.timeAndFrame.EpochArray.EpochArray = None, epoch_end: ~scarabaeus.timeAndFrame.EpochArray.EpochArray = None, tstep: float = 1, frame: ~scarabaeus.timeAndFrame.Frame.Frame = J2000 (0 - SOLAR SYSTEM BARYCENTER), noisy: bool = False, prior_range_bias=None) → ArrayWFrame#

Computes the doppler measurement between target.name and self.instrument.name (2-way doppler).

If a receiver_station is specified as an instrument (i.e. a ground station) 3-way doppler is computed instead.

Parameters:

  • target (Spacecraft) – The target spacecraft.

  • epoch_array (EpochArray, optional) – An array of epochs (times) at which the range rate measurements should be computed. If provided, overrides epoch_start, epoch_end, and tstep.

  • epoch_start (EpochArray, optional) – The starting epoch for the range ratemeasurement computations. Required if epoch_array is not provided.

  • epoch_end (EpochArray, optional) – The ending epoch for the range ratemeasurement computations. Required if epoch_array is not provided.

  • tstep (float) – The time step, in seconds, between consecutive range ratemeasurements if epoch_array is not provided. Defaults to 1 second.

  • frame (Frame, optional) – The reference frame in which the range rate computation is performed. Defaults to a J2000 Frame object.

  • noisy (bool) – Indicates if noise is added to the computed range rate measurement. Defaults to False.

generate_measurement_dataset(dataset_name: str, measurement_type: str, target: ~scarabaeus.body.Body.Body, observed_meas: ~scarabaeus.timeAndFrame.ArrayWFrame.ArrayWFrame = None, frame: ~scarabaeus.timeAndFrame.Frame.Frame = J2000 (0 - SOLAR SYSTEM BARYCENTER), noisy: bool = False, prior_range_bias=None) → list[MeasurementDataSet]#

Generates a MeasurementDataSet object that can be used by filters downstream.

Parameters:

  • dataset_name (str) – The name of the MeasurementDataSet.

  • target (Spacecraft) – The target spacecraft.

  • epoch_list (EpochArray, optional) – The epochs. Defaults to None.

  • epoch_start (EpochArray, optional) – The starting epoch. Defaults to None.

  • epoch_end (EpochArray, optional) – The end epoch. Defaults to None.

  • tstep (int, optional) – The integration timestep. Defaults to 1.

  • observed_measurements (list, optional) – The observed measurements. Defaults to None.

  • frame (Frame, optional) – The reference frame. Defaults to a J2000 Frame object.

  • noisy (bool, optional) – Indicates if noise is added to the measurements or not. Defaults to False.

Returns:

mds_list – A list of MeasurementDataSet objects representing the measurements with their key properties to be used by a filter.

Return type:

list[MeasurementDataSet]

Notes

The MeasurementDataSet output is generated in 6 steps:

  1. Computed measurements

  2. Partials

  3. Residuals

  4. Sigmas

  5. Pack everything in a list

  6. Pack the list in a MeasurementDataSet object

observed_measurements(file_name, meas_name: str = 'meas_ideal', units: ~scarabaeus.units.Units.Units = unitless, frame: ~scarabaeus.timeAndFrame.Frame.Frame = J2000 (0 - SOLAR SYSTEM BARYCENTER)) → Tuple[EpochArray, ndarray, ArrayWFrame]#

Reads measurements from a .json file.

Parameters:

  • file_name (str) – The filename of the .json file containig the measurement information.

  • meas_name (str, optional) – The name of the measurement data to access from the dictionary. Defaults to 'meas_ideal'.

  • units (Units, optional) – Units to be used to write the output AWU. Defaults to unitless.

  • frame (Frame, optional) – Frame to be used to write the output AWF. Defaults to a J2000 Frame object.

Returns:

meas_time_et, meas_sec, meas_obs – A tuple with the following values corresponding to their respective indices:

  • [0] = meas_time_etEpochArray

    The time in ephemeris time.

  • [1] = meas_Secnumpy.ndarray

    The times in seconds.

  • [2] = meas_obsArrayWFrame

    An AWF with the quantities in AWU.

Return type:

Tuple[EpochArray, numpy.ndarray, ArrayWFrame]

Notes

The writing of the json assumes or requires units and frames.

partials(target: Spacecraft, epoch: EpochArray, frame: Frame) → list#

Groups toghether the different components of measurement partials in the global H-tilde. It returns the H-tilde array for the modelled measurement.

Parameters:
Returns:

h_tilde – The H-tilde array with all measurements partials from this model by component.

Return type:

list

residuals(observed_meas: ArrayWFrame, computed_meas: ArrayWFrame) → ArrayWFrame#

Generates the measurement model’s residuals given observed and computed ArrayWFrames.

Parameters:

  • observed_meas (ArrayWFrame) – The observed measurements values (O).

  • computed_meas (ArrayWFrame) – The computed measurements values (C).

Returns:

residuals – AWF with the residual O-C.

Return type:

ArrayWFrame

write_observed_measurements(target: Spacecraft, epoch_array: EpochArray = None, epoch_start: EpochArray = None, epoch_end: EpochArray = None, tstep: float = 1, frame: Frame = None, noisy: bool = False, prior_range_bias: float = None, file_name: str = 'ideal_measurement') → None#

Generates synthetic measurements and write them as a .json file. The input of this method encapsulate the ones needed for the “computed_meas” method in each measurement model class.

Parameters:

  • target (Spacecraft) – The target spacecraft for which the range measurement is to be computed.

  • epoch_array (EpochArray, optional) – An array of epochs (times) at which the range measurements should be computed. If provided, overrides epoch_start, epoch_end, and tstep.

  • epoch_start (EpochArray, optional) – The starting epoch for the range measurement computations. Required if epoch_array is not provided.

  • epoch_end (EpochArray, optional) – The ending epoch for the range measurement computations. Required if epoch_array is not provided.

  • tstep (float, optional) – The time step, in seconds, between consecutive range measurements. If epoch_array is not provided. Defaults to 1 second.

  • frame (Frame , optional) – The reference frame in which the range computation is performed. Defaults to None.

  • noisy (bool , optional) – Whether to add noise to the computed range measurement. Defaults to False.

  • prior_range_bias (float, optional) – A prior bias value to add to the computed range measurements. Defaults to None.

  • file_name (str, optional) – The filename of the JSON in which the measurement is saved, Defaults to 'ideal_measurement'.

Return type:

None

property gs_number: int#

The ground station number

property gs_range_bias#

DESC

property instrument: Instrument#

The instrument.

property name: str#

The name of the model.

property sequence_definition: dict#

The sequence definition.

property sigma: ArrayWUnits#

The standard deviation of the measurement model.

property state_definition: dict#

The state vector definition

property station: ArrayWUnits#

The station of the measurement model.