OPASTd Based DOA Tracking Algorithm for Unfolded Coprime Linear Arrays

As a kind of array with high degree-of-freedom, unfolded coprime linear array (UCLA) shows good performance in direction-of-arrival (DOA) estimation, but there is little research on DOA tracking based on it. For this reason, an improved DOA tracking algorithm for UCLA is proposed in this paper. The algorithm updates the signal subspace through the orthonormal projection approximation and subspace tracking of deflation (OPASTd) algorithm, avoiding the computation of covariance matrix and eigenvalue decomposition. In order to avoid the global spectral peak search, the Root-MUSIC algorithm is used to obtain the DOA of the target. Compared with most traditional algorithms, the proposed algorithm has lower complexity and better real-time performance. MATLAB simulation results show that the algorithm has good performance for DOA tracking of dynamic targets, and still has high accuracy under the background of low signal-to-noise ratio (SNR). In addition, the angle tracking performance is further improved compared with the algorithm based on the projection approximation and subspace tracking of deflation (PASTd) algorithm.