Online Route Planning for Airborne Radar Networks with Multi-Target Tracking
Ye Yuan, Jianwei Wei, Wei Yi · 2024
This paper presents an online route planning strategy for airborne radar networks (ARN) with the task of multi-target tracking (MTT). A distributed covariance intersection rule is employed for tracking processing to reduce the computation and communication costs associated with data fusion. The posterior Cramer-Rao lower bound (PCRLB) regarding maneuvering parameters, including velocities and courses of airborne radars, is derived as the metric of tracking performance. By using the MinMax criterion (i.e., minimizing the PCRLB of the target with the worst predicted tracking performance), the route planning for ARN is formulated as a series of sequential optimization problems along with the tracking process. A sequential one-dimensional search algorithm with polynomial complexity is presented to solve the problems efficiently. Numerical results show that the proposed strategy can obtain a better overall MTT performance by comparing it with benchmarks.