An Application of the Orthogonal Matching Pursuit Algorithm in Space-Time Adaptive Processing

被引：11

作者：

Slesicka, Anna ^{[1
]}

Kawalec, Adam ^{[1
]}

机构：

[1] Mil Univ Technol, Fac Elect, Inst Radioelect, Gen S Kaliskiego 2, PL-00908 Warsaw, Poland

来源：

SENSORS | 2020年 / 20卷 / 12期

关键词：

space-time adaptive processing; STAP; sparse representation; MIMO radar; orthogonal matching pursuit algorithm; clutter covariance matrix; SPARSE RECOVERY; STAP METHOD; PERFORMANCE;

D O I：

10.3390/s20123468

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

The article presents a new space-time adaptive processing (STAP) method for target detection in a heterogeneous and non-stationary environment. In study it was proven that it is possible to estimate the clutter covariance matrix (CCM) in STAP by using the MIMO (Multiple Input Multiple Output) radar geometry model and the orthogonal matching pursuit (OMP) algorithm. For the estimation of spatio-temporal spectrum of clutter and target, a model of joint sparse recovery was established. As a result, clutter suppression and target detection in a heterogeneous environment will be achieved. In addition, the proposed method uses a single snapshot of the radar data cube, which eliminates the need for access to all training cells.

引用

页码：1 / 13

页数：13

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