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Adaptive resource allocation in decentralized colocated MIMO radar network for multiple targets tracking

In this paper, we present a resource-awareness decentralized colocated multiple-input multiple-output radar network for multiple targets tracking. Specifically, we develop a distributed particle filter which incorporates the scheduling of radars. Taking posterior Cramer-Rao lower bound as performance metric, we model the scheduling and power allocation problem of the radar network as a sparse optimization problem. Making use of the sparsity of the solution, the scheduling and power allocation performs jointly. We investigate the decomposable structure of the optimization problem and conduct a decentralized technique to solve it iteratively. We verify the effectiveness of the proposed decentralized radar network with the joint scheduling and power allocation (JSPA) scheme by simulation. The resource utilization is adaptively adjusted according to the states of targets and the performance demand.