An Iterative Adaptive Dictionary Learning Approach for Multiple Snapshot DOA Estimation
Weijie Tan, Xiran Feng, Weiqiang Tan, Guiyun Liu, Xinrong Ye, Chunguo Li · 2018
In this paper, we propose an iterative adaptive dictionary learning algorithm for multiple snapshot direction-of-arrival (DoA) estimation, which is based on the simultaneous orthogonal matching pursuit (SOMP). This algorithm aims to solve the off-grid problem, which mainly occurs in grid-based sparse DoA estimation. The algorithm utilizes the singular value decomposition (SVD) to make the sparse recovery method work on a lower dimensional matrix, it efficiently reduce the computation complexity. Furthermore, the algorithm uses the steepest decent method to learn the permutation parameters, it deceases the off-grid effect and improve the DoA estimation accuracy. Simulation results show that the proposed algorithm achieves the better DoA estimation performance than the grid-based sparse algorithm in off-grid case and can work well in the correlated sources case.