Joint Detection Threshold and Dwell Time Optimization for Target Tracking in Radar Networks

This paper studies a joint detection threshold and dwell time optimization strategy for target tracking in radar networks. The main objective of the proposed strategy is to minimize the total dwell time consumption while achieving the certain target detection and tracking performance with limited transmit resource. Under the integrated structure of detection and tracking, the average probability of detection in the validation region is calculated and adopted as the metric for target detection. Moreover, the predicted Bayesian Cramér-Rao lower bound incorporated with information reduction factor is derived as the target tracking criterion. Subsequently, the resulting optimization problem which is non-linear and non-convex, is solved by sequential quadratic programming technique, and the improved probabilistic data association algorithm is adopted for target detection and tracking. The simulation results demonstrate the superiority of the proposed strategy when compared to alternative benchmarks.