Optimal allocation of tracking resources

In many surveillance systems, it is required to track several prioritized targets with limited sensor resources. This paper employs mathematical programming and Kalman filtering to generate preferred sensor-to-target assignments in a generic surveillance context. The objective of most surveillance systems is to track with sufficient accuracy that appropriate decisions can be based on their output. It is assumed here that track accuracy priorities are a function of externally imposed criteria (range-to-go in an aircraft landing problem, for example). Then it is desired that the highest priority target be tracked with the greatest accuracy at any point in time. Thus, targets with the highest priorities must be tracked by those available sensors having the best accuracies. Clearly, multiple allocations are possible and attention must be directed toward efficient and tractable optimization techniques to select preferred sensor-threat assignments.