Collaborative radar node selection and transmitter resource allocation algorithm for target tracking applications in multiple radar architectures

Abstract

This article develops a collaborative radar node selection and transmitter resource allocation (CRNS-TRA) algorithm for target tracking applications in multiple radar architectures. The key mechanism of the CRNS-TRA strategy is to coordinate the radar node selection, transmit power, and dwell time of multiple radar architectures to enhance the target tracking accuracy under the constraints of several transmitter resource budgets. The analytical expression for the Bayesian Cramér-Rao lower bound (BCRLB) is derived and employed as the objective function to quantify the target tracking performance. It is shown that the CRNS-TRA problem is a mixed-integer, non-convex, and non-linear optimization problem, where the three involved parameters, that is, the radar node selection, transmit power and dwell time allocation, are all coupled in the objective function and the constraints. Subsequently, a fast and effective two-stage-based solution methodology is proposed for solving the resulting problem, which incorporates the interior point method and cyclic minimization framework. Extensive simulation results are provided to verify that the presented CRNS-TRA scheme is capable of effectively improving the target tracking performance with much lower operation time consumption when compared to other state-of-the-art resource allocation benchmarks.