Joint Power Allocation and Route Planning Scheme for Multitarget Tracking in Airborne Radar Network Under Multiuncertainty

In this article, a joint power allocation and route planning (JPARP) scheme is proposed for multitarget tracking in airborne radar network (ARN) in the presence of multiuncertainty. The main mechanism of the proposed scheme is to utilize the optimization technique to collaboratively plan route and allocate power for each airborne radar, with the aim of minimizing the power consumption of the ARN while satisfying the predetermined multiple target tracking (MTT) performance, inter-radar communication performance, and inter-radar safe distance. The Bayesian Cramer-Rao lower bound (BCRLB) and the communication data rate (CDR) are derived and adopted as metrics to evaluate the MTT performance and inter-radar communication performance, respectively. To ensure the robustness of the algorithm under multiuncertainty, we formulate the JPARP scheme as a chance-constraint programming (CCP) problem. To efficiently solve this no-convex and nondeterministic CCP problem, we relax it into an unconstrainted optimization problem. Then, a hybrid intelligent algorithm based on stochastic simulation and improved genetic algorithm (GA) is proposed to obtain a near-optimal solution. Simulation results are provided to demonstrate that the JPARP scheme is more effective in saving ARN power consumption and more robust under uncertainty than the conventional algorithm.