Adaptive Beam Scheduling Algorithm for an Agile Beam Radar in Multi-Target Tracking

An adaptive beam scheduling algorithm based on covariance control strategy is proposed for an agile beam radar in multi-target tracking applications. The algorithm uses IMMKFs (interacting multiple model Kalman filters) to track maneuvering targets. The optimal beam scheduling model is built which can schedule radar beam based on the difference between the desired covariance matrix and that of the actual covariance of each target for maintaining the target's state estimate covariance near a desired level. Two kinds of beam scheduling algorithms, the minimum mean bias criterion and the minimax bias criterion, are proposed, respectively. Simulation results show that the algorithms based on covariance control can quickly achieve the desired tracking state and allocate sensor resources effectively