Optimal proposal particle filters for detecting anomalies and manoeuvres from two line element data

Detecting the manoeuvres of satellites is an important goal within the broader task of space situational awareness. Moreover, it is advantageous to be able to detect other anomalous behaviour from satellites arising from, for instance, collisions or malfunction. The Two Line Element (TLE) data published by NORAD is the only publicly-available comprehensive source of data for satellite orbits. This paper presents a filtering approach for detecting anomalies in satellite orbits from TLE data. Particle filters are deployed to track the state of the satellites’ orbits. New TLEs that are deemed sufficiently unlikely given one’s belief of the current orbital state are designated as anomalies. The change in the orbits over time is modelled using the SGP4 model. However, it is shown that this model can have large errors in certain elements in some instances. The structure of these errors is analysed and a suitable model uncertainty is derived. The optimal proposal filter is used to further reduce the impact of the errors in the SGP4 model. This strategy improves the proposal distribution from which the particles are drawn before re-weighting, so that the resulting weights are less degenerate. The proposed techniques are evaluated on a benchmark set of 15 satellites for which an externally-obtained ground truth is available, along with simulated orbital data with inserted manoeuvres. Although this benchmark is larger than the evaluation sets used in other published work, it cannot be representative of the full population of satellites and so more emphasis is placed on the simulated data. The proposed techniques are compared against a baseline, which is similar to many previously-proposed techniques for satellite manoeuvre detection. The particle filters are shown to be superior at detecting the subtle in-track and cross-track manoeuvres in the simulated dataset. However, on the benchmark dataset, a simple baseline that focusses on the mean motion can perform equivalently to the best filters. This simple technique is likely overfit to the benchmark. • Particle filters were developed for detecting satellite manoeuvres from two-line-element data. • These particle filters were thoroughly evaluated against a baseline on real and simulated data. • The details of the uncertainty of the SGP4 propagator were explored. • Techniques were developed for handling the uncertainty of the SGP4 propagator.