Robust Integrated Route Planning and Power Scheduling for Multitarget Tracking With Decentralized Airborne Netted Radar System

In this paper, a robust integrated route planning and power scheduling (IRPPS) strategy, which takes into account both the sufficient and insufficient resource budget, is proposed for the decentralized airborne netted radar system (ANRS) with the varying network topology to perform the task of multiple targets tracking (MTT). Mathematically, from the perspective of the quality of service (QoS) criterion, achieving the minimization of network transmit resource and the satisfaction of desired MTT performance requirement simultaneously, the IRPPS strategy is then formulated as a robust constrained combinatorial optimization problem with automatic and flexible relaxation of tracking performance requirement constraint. The Bayesian Fisher information matrix (BFIM) regarding adaptable working parameters of the decentralized ANRS, which contains the heading angle and transmit power of each airborne radar node, is derived and adopted as the tracking performance metric. In order to address the formulated combinatorial optimization problem with highly coupled variables robustly, an efficient twostage solution algorithm incorporating with the improved particle swarm optimization (IPSO) and the distributed algorithm based on the average consensus dual decomposition (DACD) is put forward. Finally, numerical simulation results show the effectiveness and superiority of the proposed robust IRPPS strategy compared with other existing strategies.