Cross Validation Based Distributed Greedy Sparse Recovery for Multiview Through-the-Wall Radar Imaging
Multiview through-the-wall radar imaging (TWRI) can improve the imaging quality and target detection by exploiting the measurement data acquired from various views. Based on the established joint sparsity signal model for multiview TWRI, a cross validation (CV) based distributed greedy sparse recove...
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | International Journal of Antennas and Propagation |
| Online Access: | http://dx.doi.org/10.1155/2019/5651602 |
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| author | Lele Qu Shimiao An Yanpeng Sun |
| author_facet | Lele Qu Shimiao An Yanpeng Sun |
| author_sort | Lele Qu |
| collection | DOAJ |
| description | Multiview through-the-wall radar imaging (TWRI) can improve the imaging quality and target detection by exploiting the measurement data acquired from various views. Based on the established joint sparsity signal model for multiview TWRI, a cross validation (CV) based distributed greedy sparse recovery algorithm which combines the strengths of the CV technique and censored simultaneous orthogonal matching pursuit algorithm (CSOMP) is proposed in this paper. The developed imaging algorithm named by CV-CSOMP which separates the total measurements into reconstruction measurements and CV measurements is able to achieve the accurate imaging reconstruction and estimation of recovery error tolerance by the iterative CSOMP calculation. The proposed CV-CSOMP imaging algorithm not only can reduce the communication costs among radar units, but also can provide the desirable imaging performance without the prior information such as the sparsity or noise level. The experimental results have verified the validity and effectiveness of the proposed imaging algorithm. |
| format | Article |
| id | doaj-art-91e71c4c1e1e43e9a12f5bcdbcf0e52e |
| institution | Kabale University |
| issn | 1687-5869 1687-5877 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Antennas and Propagation |
| spelling | doaj-art-91e71c4c1e1e43e9a12f5bcdbcf0e52e2025-02-03T01:10:04ZengWileyInternational Journal of Antennas and Propagation1687-58691687-58772019-01-01201910.1155/2019/56516025651602Cross Validation Based Distributed Greedy Sparse Recovery for Multiview Through-the-Wall Radar ImagingLele Qu0Shimiao An1Yanpeng Sun2The College of Electronic Information Engineering, Shenyang Aerospace University, Shenyang 110136, ChinaThe College of Electronic Information Engineering, Shenyang Aerospace University, Shenyang 110136, ChinaThe College of Electronic Information Engineering, Shenyang Aerospace University, Shenyang 110136, ChinaMultiview through-the-wall radar imaging (TWRI) can improve the imaging quality and target detection by exploiting the measurement data acquired from various views. Based on the established joint sparsity signal model for multiview TWRI, a cross validation (CV) based distributed greedy sparse recovery algorithm which combines the strengths of the CV technique and censored simultaneous orthogonal matching pursuit algorithm (CSOMP) is proposed in this paper. The developed imaging algorithm named by CV-CSOMP which separates the total measurements into reconstruction measurements and CV measurements is able to achieve the accurate imaging reconstruction and estimation of recovery error tolerance by the iterative CSOMP calculation. The proposed CV-CSOMP imaging algorithm not only can reduce the communication costs among radar units, but also can provide the desirable imaging performance without the prior information such as the sparsity or noise level. The experimental results have verified the validity and effectiveness of the proposed imaging algorithm.http://dx.doi.org/10.1155/2019/5651602 |
| spellingShingle | Lele Qu Shimiao An Yanpeng Sun Cross Validation Based Distributed Greedy Sparse Recovery for Multiview Through-the-Wall Radar Imaging International Journal of Antennas and Propagation |
| title | Cross Validation Based Distributed Greedy Sparse Recovery for Multiview Through-the-Wall Radar Imaging |
| title_full | Cross Validation Based Distributed Greedy Sparse Recovery for Multiview Through-the-Wall Radar Imaging |
| title_fullStr | Cross Validation Based Distributed Greedy Sparse Recovery for Multiview Through-the-Wall Radar Imaging |
| title_full_unstemmed | Cross Validation Based Distributed Greedy Sparse Recovery for Multiview Through-the-Wall Radar Imaging |
| title_short | Cross Validation Based Distributed Greedy Sparse Recovery for Multiview Through-the-Wall Radar Imaging |
| title_sort | cross validation based distributed greedy sparse recovery for multiview through the wall radar imaging |
| url | http://dx.doi.org/10.1155/2019/5651602 |
| work_keys_str_mv | AT lelequ crossvalidationbaseddistributedgreedysparserecoveryformultiviewthroughthewallradarimaging AT shimiaoan crossvalidationbaseddistributedgreedysparserecoveryformultiviewthroughthewallradarimaging AT yanpengsun crossvalidationbaseddistributedgreedysparserecoveryformultiviewthroughthewallradarimaging |