Cooperative space object tracking via multiple space-based visible sensors with communication loss

Accurate and timely space object tracking is important for space surveillance missions. Among various sensors such as ground-based radars, a space-based visible (SBV) sensor has been considered as an important sensing technology to achieve the stringent goals of space surveillance due to its high-accuracy angle measurements, faster observation rates, and large sensing coverage. To achieve certain tracking accuracy requirements, multiple sensors and cooperative tracking algorithms are often used. However, communication loss is often ignored although it commonly exists in communications of different sensor applications. In this paper, a space object tracking separated extended information filter (SEIF) algorithm uses multiple space-based visible (SBV) sensors to track targets. The algorithm is evaluated through implementation in a space object tracking scenario supported by the NASA General Mission Analysis Tool (GMAT). The root mean square error is used to compare the performance of the proposed algorithm and classical algorithms, such as the EIF. The simulation results indicate that the performance of the SEIF is better than that of the EIF when there is a communications loss between different sensors.