Radio Frequency Stealth-based Optimal Radio Frequency Resource Allocation Algorithm for Multiple-target Tracking in Radar Network

In the scenario of multi-target tracking by a radar network system, a Radio Frequency (RF) stealth-based optimal RF resource allocation algorithm in radar network is proposed. Firstly, the Bayesian Cramer-Rao Lower Bound (BCRLB) of target tracking error is used as the target tracking performance index. Secondly, the optimization model is established which includes three optimization variables: radar node selection, dwell time and radiation power. In this model, the objective function is the weighted sum of the dwell time resources and radiation power resources of each radar, the constraint condition can be conclude that the BCRLB must be less than the given threshold and the system RF radiation resources must be between the upper and lower limits. Then, the two-step decomposition method is used to solve the above optimization model. The radar node selection is fixed first, then the interior point method is used to solve the simplified non-convex nonlinear optimization model, and then the Hungarian algorithm is used to determine the best radar node selection mode. The simulation results show that compared with uniform resource allocation algorithm, the proposed algorithm can effectively reduce the RF resource consumption of the radar network and improve the RF stealth performance of the system.