An experimental implementation of a particle-based dynamic sensor steering method for tracking and searching for space objects

We present practical, experimental results for a system, driven by a particle filter, that dynamically steers a space surveillance sensor to track and search for resident space objects. In contrast to traditional Kalman-filter-based trackers, this system can exploit scheduled observations where the target is not found within the field of view. Furthermore, real-time observation-evaluation enables the system to immediately respond to these events by conducting a limited search. We describe the system and report the results of a recent field trial using a computer-controlled Raven-class electro-optical sensor to track objects using two-line element sets (TLEs) of various ages. Even for quite old TLEs - in some cases over six months old - the system demonstrates successful, automatic reacquisition.