Sensor Tasking for multi-sensor Space Object Surveillance

Efficient sensor tasking is a crucial step in building up and maintaining a catalog of space objects at the highest possible orbit quality. With increased sensing capabilities, also the amount of objects that can be and are thought to be kept in the catalog is increasing. Realistic object numbers can easily reach over 100000 objects. It is crucial to note that for efficient collision avoidance and surveillance, individual information of those objects is sought rather than merely statistical information. Sensor resources are necessarily of a much smaller number compared to the number of objects. The object probability density function, and hence how good a catalog is, is influenced by the number of observations, the spacing and their quality. This makes sensor tasking a crucial step in order to ensure the best possible space object catalog. The best possible space object catalog can be defined as fulfilling a number of criteria. In the approach in this paper reformulates sensor tasking as an optimization problem. A cost function that is apt to the SSA tracking and cataloging problem is derived. The method is flexible enough to being able to incorporate multiple sensors with different observation schedules. The method can operate on a known a priori catalog of objects or be started on first principles. Computational feasible ways to evaluate the optimization are are shown and evaluated. The result shows a highly efficient sensor tasking scheme.