10. RangeIdeal#

class RangeIdeal(name: str, instrument: scbt.Instrument, sigma: ArrayWUnits = None, gs_range_bias=None, state_definition=None, sequence_definition=None)#

Bases: Measurement

Models the ideal range measurement model. It generates ranging observables between an observer and a target. The ranging observables are expressed in km and refers to the norm of the relative position vector between the two (plus noise, if added).

Parameters:

name (str) – name of the measurement model
instrument (scb.Instrument) – instrument object from scarabaeus. An ‘antenna’ instrument is used for radiometric measurement models.
sigma (scb.ArrayWUnits, optional) – Measurement standard deviation. Optional, defaults to None.
gs_range_bias (float, optional) – ground station range bias. Optional, defaults to None.
state_definition (list, optional) – StateVector definition list. Optional, defaults to None.
sequence_definition (list, optional) – sequence definition list. Optional, defaults to None.

:raises RuntimeError(`'The model name should consistently begin with 'GS``’ followed by a number and a space (e.g., ‘GS1 ``', '``GS2 ``') to designate the order of ground stations. The provided name does not adhere to this criterion.'): | Raised when the name for the measurement model is not consistent with standardized notation used across the rest of the code. :raises RuntimeError(``’multiple units are extracted from the measurements.’:py:class:`): | Raised when the units extracted from the measurements are not consistent with each other. :raises RuntimeError(`’Please provide an EpochArray or provide start and end Epochs.’``:py:class:`): | Raised when the time on which to generate measurements is not an EpochArray object or is not passed as a begin and end pair.

See also

scarabaeus.Measurement: parent class of each specific measurement model.

Examples

# import libraries
import scarabaeus as scb

# Generate an antenna object and link it to an existing orbiter
Orbiter_spice_id = -64
antenna_sc = scb.Antenna("Antenna_for_radiometric", spice_id = Orbiter_spice_id)
Orbiter.addInstrument([antenna_sc])
Doppler_transmit_frequency = scb.ArrayWUnits(
    8.8 * 10**9, sec**-1
)

# Generate a Centroid measurement model
range_sigma = scb.ArrayWUnits(1e-3, km)

# Generate a ground-station object
GS1 = scb.GroundStation("DSS-14")

# Generate an ideal range measurement model
Range_GS1 = scb.RangeIdeal(
    name="GS1 Ideal Range Model", instrument=GS1, sigma=range_sigma
)

# Write observed measurements in .json format
Range_GS1.write_observed_measurements(
    target=Orbiter,
    epoch_array=epoch_array_range,
    frame=J2000,
    noisy=True,
    prior_range_bias=None,
    file_name="ideal_range",
)

# Read observed measurement in .json format
obs_quantities_range = Range_GS1.observed_measurements(
    file_name="data/dwn_data/ideal_range.json", meas_name="meas_ideal", units=km
)

# Generate computed measurements on a trajectory
computed_range_GS1 = Range_GS1.computed_measurements(
    target=Orbiter_perturbed,
    epoch_array=epoch_range_GS1_et,
    frame=J2000,
)

# Compute the partials
range_GS1_partials = Range_GS1.compute_partials(
    target=Orbiter_perturbed, epoch_array=epoch_range_GS1_et, frame=J2000
)

# Compute the residuals
residuals_range_GS1 = Range_GS1.residuals(observed_range_GS1, computed_range_GS1)

# Generate a measurement dataset
range_dataset_GS1 = Range_GS1.generate_measurement_dataset(
    "GS1 Range",
    measurement_type="range",
    target=Orbiter_perturbed,
    observed_meas=obs_quantities_range,
)

Attributes

`instrument`	The instrument.
`name`	The name of the model.
`sigma`	Standard deviation of the measurement model.

Methods

`compute_h_tilde_dv_man`()	This method generate the portion in the h_tilde matrix relative to the partial of the ideal range measurement model with respect to the maneuver DV components.
`compute_h_tilde_eta_srp`()	This method generate the portion in the h_tilde matrix relative to the partial of the ideal range measurement model with respect to the srp scaling factor (eta_srp).
`compute_h_tilde_gs_location`(relative_state)	This method generate 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)	This method generate the portion in the h_tilde matrix relative to the partial of the ideal range measurement model with respect to the position components.
`compute_h_tilde_range_bias`()	This method generate the portion in the h_tilde matrix relative to the partial of the ideal range measurement model with respect to the range bias.
`compute_h_tilde_vel`()	This method generate the portion in the h_tilde matrix relative to the partial of the ideal range 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, ...])	Compute the range measurement between an observer and a target.
`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])	This method 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() → list#

This method generate the portion in the h_tilde matrix relative to the partial of the ideal range measurement model with respect to the maneuver DV components.

Returns:: The (3,) vector the partial derivatives of the measurement model by the position maneuver DV components
Return type:: np.array

References