Introduction

What is SORTS

SORTS stands for Space Object Radar Tracking Simulator (SORTS). It is a collection of modules designed for research purposes concerning the tracking and detection of objects in space. Its ultimate goal is to simulate the tracking and discovery of objects in space using radar systems in a very general fashion. Therefor it can not only be used for simulating the performance of radar systems but be used to plan observations and schedule campagins.

Feature list

  • Vast library of usage examples

  • Quick calculation of passes over a radar system

  • Easy simulation of observed variables of hard targets with radar systems (range, range rate, radar cross section, signal to noise ratio, …) given an arbitrary radar and radar observation schema

  • Definition of arbitrary radar control systems

  • Definition of arbitrary scheduler systems that manage radar-controllers

  • Pre-defined library of radar systems, radar survay patterns, standard radar controllers and schedulers

  • Standardized interface to a collection of propagators

  • Allows modification of any level of a simulation trough sub-classing the basic models

  • Large collection of helper functions for simulation to automate e.g. MPI-trivial parallelization and disk-caching

  • Execution time and memory usage profiler compatible with most base models

  • Logging compatible with most base models

  • Frame transformations implemented trough Astropy

  • Time handling implemented trough Astropy

  • All time-critical calculations implemented using numpy to accelerate calculation

  • Predefined error models such as ionospheric ray bending and coded transmission matched filter errors

  • Ray-tracing simulation of radar signals trough the ionosphere using pyglow

  • Measurement Jacobian calculation and linearized orbit error calculation and propagation

  • Ability to plan measurement campaigns using the output from a scheduler simulation

  • Collection of predefined population formats for loading e.g. TLE catalogs

  • Correlation algorithms for correlating measurement data to a population

  • Input/Output package for writing and reading standardized data formats e.g. CCSDS TDM files

  • Large collection of plotting functions for quick visualization

  • Interpolation methods for propagation optimization

  • …

Example

Finding all passes of a space object over a radar system

#!/usr/bin/env python

import numpy as np
import pyorb

import sorts
from sorts.propagator import SGP4

eiscat3d = sorts.radars.eiscat3d

prop = SGP4(
    settings = dict(
        out_frame='ITRS',
    ),
)

orb = pyorb.Orbit(
    M0 = pyorb.M_earth,
    direct_update=True,
    auto_update=True,
    degrees=True,
    a=7200e3,
    e=0.05,
    i=75,
    omega=0,
    Omega=79,
    anom=72,
    epoch=53005.0,
)
print(orb)

t = sorts.equidistant_sampling(
    orbit = orb,
    start_t = 0,
    end_t = 3600*24*1,
    max_dpos=1e4,
)

states = prop.propagate(t, orb.cartesian[:,0], orb.epoch)

passes = eiscat3d.find_passes(t, states)

for txi in range(len(eiscat3d.tx)):
    for rxi in range(len(eiscat3d.rx)):
        for ps in passes[txi][rxi]: print(ps)