[author_cn_name].[cn_title][J].空军工程大学学报:自然科学版,[year_id],[volume]([issue]):[start_page]-[end_page] 基于2D-SOONE算法的MIMO稀疏面阵二维成像-Sparse MIMO Planar Array 2D Imaging Based on 2D SOONE Algorithm
Sparse MIMO Planar Array 2D Imaging Based on 2D SOONE Algorithm
中文关键词: MIMO  二维成像  二维联合稀疏  2D-SOONE
英文关键词: two dimensional imaging  two dimensional joint sparse  2D-SOONE
陈桥,童宁宁,胡晓伟,丁姗姗,胡仁荣 空军工程大学防空反导学院,西安,710051 
摘要点击次数: 65
全文下载次数: 75
      Sparse recovery algorithm can realize sparse MIMO planar array two dimensional imaging. When the traditional 1D-CS algorithm is adopted to treat with the dimension sorting in processing, there will be a loss of the coupling information, the migration of cell will be caused by, the image is poor in quality, and time is too long in operation. For the reason mentioned above, the structure characteristics of MIMO planar array are studied in this paper. The paper analyzes the joint sparse feature of the two dimensional data accepted by MIMO and realizes the joint reconstruction of the two dimensional data by adopt 2D-SOONE algorithm. The algorithm uses sequential order one negative exponential function instead of Gaussian function of the traditional SL0 algorithm, extends to the two dimensions and solved by gradient projection, and has the performance of the two dimensional joint reconstruction, and the precision of reconstruction is improved. Through experiments, the imaging effect of the algorithm for MIMO sparse array is simulated under different array sparsity and SNR. The simulation results show that the 2D-SOONE algorithm suppresses the cell migration problem of the traditional 1D CS algorithm, and reduces the operation time. The imaging quality is better than that of the 2D-SL0 algorithm.
查看全文   查看/发表评论  下载PDF阅读器