Low probability of intercept‐based cooperative node selection and transmit resource allocation for multi‐target tracking in multiple radars architecture - Lintao Ding; Chenguang Shi; Fei Wang; Jianjiang Zhou (IET Signal Processing)
Abstract A low probability of intercept (LPI)‐based cooperative node selection and transmit resource allocation (CNS‐TRA) strategy is proposed for multi‐target tracking in multiple radars architecture (MRA). The key idea of the proposed CNS‐TRA strategy is to coordinate the radar node selection and the transmit resource that is, dwell time, transmit power, and effective bandwidth allocation to improve the LPI performance, under the constraints of predefined target tracking accuracy requirement and several resource budgets. By incorporating the above controllable parameters, the Bayesian Cramér‐Rao lower bound is calculated and used as the accuracy metric for target tracking. Subsequently, this paper develops a fast and effective two‐stage‐based solution methodology to solve the resulting non‐convex and non‐linear optimisation problem. Specifically, the optimisation problem can be decomposed into two sub‐problems, that is, the radar node selection sub‐problem and the transmit resource allocation sub‐problem. The active‐set method and the interior point approach are utilised to solve those two sub‐problems, respectively. Simulation results demonstrate that the CNS‐TRA strategy has superiority over other existing algorithms and can achieve better LPI performance for MRA.