Multi-view TWRI scene reconstruction using a joint Bayesian sparse approximation model

被引:0
作者
Tang, V. H. [1 ]
Bouzerdoum, A. [1 ]
Phung, S. L. [1 ]
Tivive, F. H. C. [1 ]
机构
[1] Univ Wollongong, Sch Elect Comp & Telecommun Engn, Wollongong, NSW 2522, Australia
来源
COMPRESSIVE SENSING IV | 2015年 / 9484卷
关键词
Multi-view through-the-wall radar imaging; wall clutter mitigation; compressed sensing; joint Bayesian sparse recovery; WALL CLUTTER MITIGATION; RADAR;
D O I
10.1117/12.2180096
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
This paper addresses the problem of scene reconstruction in conjunction with wall-clutter mitigation for compressed multi-view through-the-wall radar imaging (TWRI). We consider the problem where the scene behindthe-wall is illuminated from different vantage points using a different set of frequencies at each antenna. First, a joint Bayesian sparse recovery model is employed to estimate the antenna signal coefficients simultaneously, by exploiting the sparsity and inter-signal correlations among antenna signals. Then, a subspace-projection technique is applied to suppress the signal coefficients related to the wall returns. Furthermore, a multi-task linear model is developed to relate the target coefficients to the image of the scene. The composite image is reconstructed using a joint Bayesian sparse framework, taking into account the inter-view dependencies. Experimental results are presented which demonstrate the effectiveness of the proposed approach for multi-view imaging of indoor scenes using a reduced set of measurements at each view.
引用
收藏
页数:10
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