JPBA of ARN for target tracking in clutter

Abstract

Networked radar systems can be used to improve target tracking performance. In the asynchronous radar network (ARN) system, the radars may work at different sampling rates, bringing difficulties in resource allocation. In this study, the authors propose a joint power and bandwidth allocation (JPBA) strategy to track a target by ARN in clutter. First, they build an asynchronous resource allocation model, in which a periodic allocation strategy is suggested. Second, they derive the Bayesian Cramer–Rao lower bound by incorporating the information reduction factor as a performance metric for the JPBA strategy. Third, the asynchronous power and bandwidth allocation optimisation problem are formulated by minimising the tracking root-mean-square error with given power and bandwidth budgets, which is non-convex but monotonic. Finally, by introducing the branch-reduce-and-bound algorithm, a global solution to the optimisation problem is obtained. Numerical results verify the validity of the proposed JPBA strategy for target tracking by ARN.