Joint Resource and Detection Threshold Optimization for Maneuvering Targets Tracking in Colocated MIMO Radar Network

Compared with monostatic phased array radar, a colocated multiple-input–multiple-output (MIMO) radar network (CMRN) that owns richer controllable resources is able to offer superior tracking performance. In this article, for targets tracking in a cluttered environment with the CMRN, a joint detection threshold optimization and transmit resource allocation (JDTO-TRA) algorithm is proposed to simultaneously maximize the tracking performance and minimize the resource consumption, whose key mechanism is to adaptively control the working parameters at both transmitters and detectors via optimization technique. To be more specific, we first formulate the JDTO-TRA strategy as a biobjective optimization problem, where both the tracking performance and the resource consumption are considered in the objective function. The analytical expression for the posterior Cramér–Rao lower bound incorporated with information reduction factor, which is caused by the measurement origin uncertainty, is given and adopted as the tracking performance metric, and the total transmit energy of the CMRN is employed as the resource consumption metric. Hereafter, to tackle the formulated mixed-integer and nonconvex problem effectively, an iterative and efficient two-step solution technique incorporating the simulated-annealing-based hybrid particle swarm optimization and the cyclic minimization algorithm is proposed, where the radar-target assignment, the subarray number and the transmit energy of each activated colocated MIMO radar, and the false alarm rate of the target can be controlled jointly and adaptively. Numerical simulation results are provided to demonstrate the effectiveness as well as the advantages of the JDTO-TRA algorithm compared with other popular existing algorithms.