Informative radar selection for tracking in radar networks

In radar networks, radar selection has played a more and more important role. Many radar selection methods have been proposed. Recently a novel method which is based on sparsity-aware matrix decomposition has been proposed to identify informative sensors for target tracking. However, this method had stringent constraints and was under the assumption of known noise parameters in the sensing field. In this paper, we first use radar measurement model to deploy the method in radar networks. Second, we consider noise with unknown parameters existing in the sensing field. Then, we propose two methods to select the informative radars based on setting a threshold for the decomposed matrix and adjusting the parameters in the matrix deflation algorithm, respectively. Finally, we verify our proposals via numerical simulations.