Application Analysis of Compressive Sensing/sampling Theory on Source Localization

被引：0

作者：

Han, Xuebing ^{[1
]}

Qiu, Chunhui ^{[2
]}

Jiang, Zhaojun ^{[1
]}

机构：

[1] AF Airborne Acad, Guilin, Peoples R China

[2] Equipment Dept Beijing Mil Region, Beijing, Peoples R China

来源：

MEASUREMENT TECHNOLOGY AND ITS APPLICATION, PTS 1 AND 2 | 2013年 / 239-240卷

关键词：

Compressive sensing/sampling; restricted isometry property; Direction-of-arrival estimation; super-resolution;

D O I：

10.4028/www.scientific.net/AMM.239-240.1409

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we consider the source localization problem with Compressive Sensing/Sampling (CS) Theory. CS Theory asserts one can reconstruct sparse or compressible signals from a very limited number of measurements. A necessary condition relies on properties of the sensing matrix such as the restricted isometry property (RIP). This paper explains why sparse construction can be used in source localization with RIP conception.

引用

页码：1409 / +

页数：2

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