Wavelet-Based Compressive Imaging of Sparse Targets

被引：82

作者：

Anselmi, Nicola ^{[1
]}

Salucci, Marco ^{[1
,2
]}

Oliveri, Giacomo ^{[1
]}

Massa, Andrea ^{[1
,2
]}

机构：

[1] Univ Trento, ELEDIA Res Ctr, DISI, I-38123 Trento, Italy

[2] UMR CNRS 8506, ELEDIA Offshore Lab, Lab Signaux & Syst, L2S, F-91192 Paris, France

来源：

IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION | 2015年 / 63卷 / 11期

关键词：

Bayesian compressive sampling; first-order Born approximation (BA-I); inverse scattering; microwave imaging; wavelets; OF-ARRIVAL ESTIMATION; INVERSE SCATTERING; RECONSTRUCTION; MITIGATION; MULTISCALE; ARRAYS;

D O I：

10.1109/TAP.2015.2444423

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：

The application of the compressive sensing (CS) paradigm to retrieve non-single-pixels contrast profiles is discussed. By exploiting a wavelet representation to model complex scatterer distributions with sparse vectors of coefficients, an efficient Bayesian CS (BCS) strategy is adopted to solve the arising inverse scattering problem. A set of representative numerical examples is presented to illustrate the advantages and the limitations of the proposed approach also with respect to comparable state-of-the-art inversion methods.

引用

页码：4889 / 4900

页数：12

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