A Cooperative Node and Waveform Allocation Scheme in Distributed Radar Network for Multiple Targets Tracking

The waveform agile radars generally provide more flexibility in different sensing scenarios than the traditional radars with fixed waveforms. In this paper, to get more degree of freedom, we consider cooperatively allocate nodes and corresponding waveforms of multistatic radar network with individual nodes transmit variable waveforms. We model the joint nodes and waveforms allocation scheme as a weighted sparse optimization problem. The problem aims at minimizing the cost of the allocation of waveforms while satisfies the predetermined tacking accuracy demands of each targets, where the Posterior Cramér-Rao Lower Bound (PCRLB) is utilized to evaluate the tracking performance. We assume that all the radar nodes are organized in a fully distributed fashion, where only neighboring information exchange is conducted. Therefore, we develop a distributed optimization method based on primal dual algorithm to solve the resultant optimization problem. Simulation results illustrate the effectiveness of the proposed allocation model and optimization algorithm.