Successful space domain awareness (SDA) requires maintaining track custody of cooperative and noncooperative cislunar space objects (CSOs) through both ballistic and maneuvering trajectories. The surveillance of CSOs is particularly challenging due to the underlying chaotic multi-body dynamics, which makes uncertainty propagation more difficult when compared to Keplerian orbits. While methods exist for tracking cooperative spacecraft using high accuracy range measurements, the problem of passive noncooperative maneuvering CSO tracking has received considerably less attention. In this paper, CSO motion is modeled as a jump Markov system (JMS), where the CSO modality is unknown and subject to random switching. A novel adaptive Bayesian filter is proposed and shown to successfully maintain CSO track custody through both ballistic and maneuvering phases of an Artemis I-like trajectory.
Adaptive Gaussian Mixture Filtering for Multi-sensor Maneuvering Cislunar Space Object Tracking
J Astronaut Sci
08.01.2025
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Cislunar space , Space domain awareness , Maneuvering object tracking , Nonlinear estimation , Negative information , Random finite sets Engineering , Aerospace Technology and Astronautics , Mathematical Applications in the Physical Sciences , Space Sciences (including Extraterrestrial Physics, Space Exploration and Astronautics)
Adaptive Gaussian Mixture Filtering for Multi-sensor Maneuvering Cislunar Space Object Tracking
Springer Verlag | 2025
|NTRS | 1970
Elsevier | 2025
|