期刊名称:International Journal of Antennas and Propagation
印刷版ISSN:1687-5869
电子版ISSN:1687-5877
出版年度:2017
卷号:2017
DOI:10.1155/2017/6862852
出版社:Hindawi Publishing Corporation
摘要:Sparse matrix reconstruction has a wide application such as DOA estimation and STAP. However, its performance is usually restricted by the grid mismatch problem. In this paper, we revise the sparse matrix reconstruction model and propose the joint sparse matrix reconstruction model based on one-order Taylor expansion. And it can overcome the grid mismatch problem. Then, we put forward the Joint-2D-SL0 algorithm which can solve the joint sparse matrix reconstruction problem efficiently. Compared with the Kronecker compressive sensing method, our proposed method has a higher computational efficiency and acceptable reconstruction accuracy. Finally, simulation results validate the superiority of the proposed method.