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The resource-aware design is of great importance for the distributed multiple-input multiple-output (MIMO) radar in military applications, where multiple missions need to be fully and simultaneously performed constrained by the resource budget. Aiming at the joint of tracking existing targets and detecting new threats, a sensor scheduling integrated with power and bandwidth allocation strategy is put forward. The predicted posterior Cramer-Rao lower bound (PCRLB) in the worst case and the probability of detection are integrated as the optimization metric. Since such a problem is NP-hard, a modified particle swarm optimization (MPSO) for the sensor selection; embed with the greedy idea for the power and bandwidth allocation, is proposed for the solution exploration. The numerical simulations demonstrate that the MPSO is capable of providing close performance to the exhaustive search based method. More importantly, it possesses a lower computational burden and achieves better results compared with multi-start local search (MSLS)-based method.

Sensor Scheduling and Resource Allocation in Distributed MIMO Radar for Joint Target Tracking and Detection