Joint Detection Threshold Optimization and Transmit Resource Allocation for Targets Tracking in Clutter with Colocated MIMO Radar Networks

In this paper, for targets tracking in cluttered environment with colocated MIMO radar network (CMRN), a joint detection threshold optimization and transmit resource allocation (JDTO- TRA) algorithm is proposed to simultaneously maximize tracking performance and minimize resource con-sumption, whose key mechanism is to adaptively control the working parameters at both the transmitters and the detectors via optimization technique. To be more specific, we formulate the JDTO- TRA as a mixed-integer and non-convex bi-objective optimization problem that is generally intractable. The analytical expression for the posterior Cramer-Rae lower bound (PCRLB) incorporated with information reduction factor (IRF), which is caused by the measurement origin uncertainty, under covari-ance intersection (CI) fusion rule is calculated and adopted as the tracking performance metric. To tackle the formulated problem effectively, we propose an iterative and efficient two-step solution technique incorporating the simulated annealing (SA)-based hybrid particle swarm optimization (HPSO) and the cyclic minimization algorithm (CMA), where the radar-target assignment, the sub-array number and transmit energy of each activated colocated MIMO radar, and the false alarm rate (FAR) of target with respect to radar can be controlled jointly and adaptively. Numerical simulation results are provided to demonstrate the effectiveness as well as the advantages of our proposed JDTO- TRA algorithm compared with other four existing benchmark algorithms.