A Sensor Selection Algorithm with Improved Accuracy Constraint for Maneuvering Target Tracking

To control the sensor system radiation risk and satisfy the maneuvering target tracking requirement, a sensor selection algorithm with improved accuracy constraint for maneuvering target tracking is proposed. Firstly, the posterior Cramr-Rao lower bound (PCRLB) is utilized to assess the tracking performance. Then multiple model PCRLB is presented to calculate the PCRLB of maneuvering target. Secondly, tracking accuracy is treated in a probabilistic manner in the improved accuracy constraint. Then the improved accuracy constraint can be converted to a deterministic constraint by the given desired tracking accuracy and probability. Finally, as the active sensor obtain the target measurement by emitting energy that can betray their existence and location, radiation control policy is presented to minimize the times of active sensor selection. Simulation results prove the effectiveness of the proposed algorithm.