The complexity of combat environment makes it more and more difficult for traditional monostatic radar to track targets continuously. The radar network technology can effectively improve the overall tracking performance. Therefore, in the distributed radar network scenario, a joint sensor selection, bandwidth and dwell time resource optimal allocation algorithm is proposed for multi-target tracking. At first, the local state is estimated and corrected by the Covariance Intersection (CI) fusion strategy. Then the algorithm aims to minimize the predicted Bayesian Cramer-Rao Lower Bound (BCRLB) of the worst target tracking mean square error. And a joint radar node selection, bandwidth and dwell time resource optimization model is established for multi-target tracking in distributed radar network. The radar node is selected with BCRLB as the metric criterion first. Then the optimal model after sensor selection is carried out by using the cyclic minimum algorithm and the minimax algorithm. Simulation experiments show that compared with the uniform resource allocation and single-resource optimal allocation algorithms, the proposed algorithm can effectively improve the multi-target tracking accuracy under the limited resources.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.