Robust Tracking of Multiple Targets Subspace Based on Distributed Array Networks

Robust subspace tracking is a real-time solution for suppressing harsh interference and estimating the target subspace in complex electromagnetic environments. In this article, a robust and decentralized subspace tracking method is proposed. The multisensor array is divided into a number of nodes, each attached with a processor and no central processing unit (CPU) is deployed. In order to reduce the impact of a burst pulse, a robust real-time update algorithm of the subspace is designed through the weighted least squares method. The optimization model established in this article is robust to synchronization error. Then a subspace real-time update algorithm is proposed based on the average consensus (AC) method that integrates the information of distributed arrays. The computational complexity and convergence properties of the proposed algorithm are also investigated. Simulation results show that the proposed approach converges to the subspace estimation error by an order of magnitude compared with the single-node algorithm.