Bayesian Sparse Estimation of Migrating Targets in Autoregressive Noise for Wideband Radar

被引：0
|
作者：
Bidon, Stephanie [1 ]
Besson, Olivier [1 ]
Tourneret, Jean-Yves [2 ]
Le Chevalier, Francois [3 ]
机构：
[1] Univ Toulouse, DEOS ISAE, Toulouse, France
[2] Univ Toulouse, IRIT ENSEEIHT TeSA, Toulouse, France
[3] Delft Univ Technol, MS3, Delft, Netherlands
来源：
2014 IEEE RADAR CONFERENCE | 2014年
关键词：
MODELS;
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：
In recent work we showed the interest of using sparse representation techniques to estimate a target scene observed by wideband radar systems. However the principle was demonstrated in a white noise background only. In this paper, we present an extended version of our sparse estimation technique that attempts to take into account the (possible) presence of diffuse clutter. More specifically, an autoregressive model is considered for the noise vector. Performance of the technique is studied on synthetic and experimental data. Pertinence of the noise model is discussed.
引用
收藏
页码：579 / 584
页数：6
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