Collaborative detection and power allocation framework for target tracking in multiple radar system

In reality, multiple radar system (MRS) may have some limited resource, such as the data computation capacity of the fusion center and the transmit energy of each radar. To better exploit its limited system resource, a collaborative detection and power allocation (CDPA) scheme is developed for the application of target tracking in clutter. The basis of the CDPA scheme is to use optimization technique to control the false alarm rate (FAR) and transmit power of each radar in view of the aforementioned resource constraints, while achieving better target state estimation accuracy. The Bayesian Cramer-Rao lower bound is derived, relaxed, and subsequently utilized, as the optimization criterion for the CDPA strategy. The resulting nonlinear and nonconvex optimization problem consists of two adaptable vectors, one for FAR selection and the other for power allocation. By introducing an auxiliary vector, a fast two-step solution technique is presented to jointly select the FAR and distribute the transmit power. Simulation results demonstrate that, with given data computation capability and system total power budget, the CDPA scheme can evidently expand the detection range, increase the resource utilization efficiency of the MRS, and improve the target tracking accuracy.