Sensor tasking for search and catalog maintenance of geosynchronous space objects

The space object catalog provides orbital state and characteristic information of space objects for critical applications in space situational awareness. Maintaining accurate states for all objects in the catalog is essential, but it leads to large loads on sensors and limits the time available to search for new objects. This study proposes a novel sensor tasking method for search and catalog maintenance of space objects in Geosynchronous Earth Orbit (GEO). This new framework formulates sensor tasking as a multi-objective optimization problem. It seeks an optimal balance between sensor resources to search for new objects and to maintain precise state estimates for all objects in the catalog. In order to maintain custody of newly detected targets, an evidence-based decision-making method is used to effectively prompt follow-on tracking. The labeled mull-Bernoulli filter is employed to track existing and new space objects and provide refined orbital state estimation. Simulation results are presented, in which 100 cataloged GEO objects and 200 new GEO objects are tracked using a space-based sensor placed on a Sun-synchronous orbit.