ssapy.correlate_tracks

Provides classes and functions for orbital tracking, hypothesis testing, angle wrapping, and fitting satellite observations to orbital models.

Functions

combinatoric_lnprior(nsat, ntrack, ndet)	Prior probability of assigning detections to tracks of satellites.
data_for_satellite(data, satIDList)	Extract data for specific satID.
fit_arc(arc, guess[, verbose, propagator, ...])	Fit an orbit to an arc.
fit_arc_blind(arc[, verbose, mode, priors, ...])	Fit an orbit to an arc.
fit_arc_blind_via_track(arc[, propagator, ...])	Fit a series of detections using the Track interface.
fit_arc_with_gaussian_prior(arc, mu, cinvcholfac)	Fit an orbit to an arc.
iterate_mht(data, oldmht[, nminlength, trimends])	Iterates and refines the Multiple Hypothesis Tracking (MHT) process by updating tracks and generating new hypotheses.
make_optimizer(mode, param[, lsq])	Creates and returns an optimizer object or function for orbital parameter estimation based on the specified mode and configuration.
make_param_guess(rvguess, arc[, mode, orbitattr])	Generates an initial parameter guess for orbital estimation based on the provided mode, observation arc, and optional orbital attributes.
orbit_to_param(orbit[, mode, orbitattr, ...])	Convert Orbits to parameters.
param_to_orbit(param[, mode, orbitattr])	Convert parameters to Orbits.
radeczn(orbit, arc, **kw)	Compute right ascension, declination, range, rates, and anomaly wraps.
summarize_tracklet(arc)	Compute mean ra/dec, uncertainty in mean, proper motion, uncertainty for a short arc.
summarize_tracklets(data[, posuncfloor, ...])	Add fields to default data set to accommodate MHT fitting.
time_ordered_satIDs(data[, with_time, order])	Give satIDs in data in order of observation.
wrap_angle_difference(dl, wrap[, center])	Wraps an angle difference to a specified range.

Classes

CircVelocityPrior([sigma])	Gaussian prior that log(GM/r/v^2) = 0.
GaussPrior(mu, cinvcholfac, translator)	Gaussian prior on parameters.
Hypothesis(tracks[, nsat])	Assignment of detections to multiple tracks.
MHT(data[, nsat, truth, hypotheses, ...])	Multiple Hypothesis Tracking of many hypotheses explaining data.
Track(satIDs, data[, guess, initial_lnprob, ...])	Set of observations to be fit as an object moving through space.
TrackBase(satIDs, data[, volume, mode, ...])	Set of observations fit together as an orbital track.
TrackGauss(satIDs, data, param, covar, chi2)	Set of observations to be fit as an object moving through space.
VolumeDistancePrior([scale])	Prior on range like r^2*exp(-r/scale), preferring larger distances where there is more volume.
ZeroRadialVelocityPrior([sigma])	Gaussian prior that v_R = 0.

Class Inheritance Diagram