Bilinear Compressed Sensing for Array Self-Calibration

被引：0
|
作者：
Friedlander, B. [1 ]
Strohmer, T. [2 ]
机构：
[1] Univ Calif Santa Cruz, Dept Elect Engn, Santa Cruz, CA 95064 USA
[2] Univ Calif Davis, Dept Math, Davis, CA 95616 USA
来源：
CONFERENCE RECORD OF THE 2014 FORTY-EIGHTH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS | 2014年
关键词：
DOA;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
We consider array self-calibration algorithms for direction finding in the presence of unknown complex sensor gains. By exploiting the sparsity in the azimuth domain, we can utilize methods developed in the context of compressive sensing. A self-calibration algorithm is proposed that alternates between solving a joint-sparse optimization problem and estimating the unknown array gains. Furthermore, for the case of fully correlated signals we introduce a convex programming algorithm based on bilinear compressive sensing.
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页码：363 / 367
页数：5
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