On Exploring Sparsity in Widely Separated MIMO Radar

被引:0
|
作者
Petropulu, Athina P. [1 ]
Yu, Yao [1 ]
Huang, Junzhou [2 ]
机构
[1] Rutgers State Univ, Dept Elect & Comp Engn, Piscataway, NJ 08854 USA
[2] Univ Texas Arlington, Dept Comp Sci & Engn, Arlington, TX 76019 USA
关键词
compressive sampling; MIMO Radar; target localization; sparsity; group sparsity; SIGNAL RECOVERY; ANTENNAS; TIME;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The scenario of widely separated multi-input multi-output (MIMO) radar is considered. For a small number of targets, the target returns are sparse in the target space. First, a decoupled Lasso approach is proposed, which by exploiting the structure of the basis matrix decomposes the large size problem into a number of smaller size problems, thus reducing computational complexity. Second, it is shown that by reordering the columns of the basis matrix, group sparsity can be introduced to the returns. This structure can be exploited by a group Lasso approach to achieve significant performance gains.
引用
收藏
页码:1496 / 1500
页数:5
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