Joint Route and Resource Optimization for Multiple Targets Tracking in Decentralized Airborne Networked Radars

In this article, a strategy of joint route and resource control (JRRC) strategy is present for decentralized airborne networked radar (ANR) in multi-target tracking (MTT) application. The Bayesian Fisher information matrix (BFIM) regarding adaptable working parameters of decentralized ANR, which contains the heading angle and power resource of airborne radars, is derived and adopted to measure the tracking accuracy. Considering the quality of service (QoS) scheme, which consumes the minimization of network resource and meets the desired MTT performance requirement at the same time, the JRRC strategy is then constructed to be a mathematical optimization model. In order to address the formulated problem with multiple optimization variables, a two-stage solution method incorporating the particle swarm optimization and the distributed algorithm based on the average consensus dual decomposition is developed. Numerical simulations show the validity of the JRRC strategy.