Augmented Lagrange Based on Modified Covariance Matching Criterion Method for DOA Estimation in Compressed Sensing
A novel direction of arrival (DOA) estimation method in compressed sensing (CS) is presented, in which DOA estimation is considered as the joint sparse recovery from multiple measurement vectors (MMV). The proposed method is obtained by minimizing the modified-based covariance matching criterion, wh...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/241469 |
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| _version_ | 1832555949991133184 |
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| author | Weijian Si Xinggen Qu Lutao Liu |
| author_facet | Weijian Si Xinggen Qu Lutao Liu |
| author_sort | Weijian Si |
| collection | DOAJ |
| description | A novel direction of arrival (DOA) estimation method in compressed sensing (CS) is presented, in which DOA estimation is considered as the joint sparse recovery from multiple measurement vectors (MMV). The proposed method is obtained by minimizing the modified-based covariance matching criterion, which is acquired by adding penalties according to the regularization method. This minimization problem is shown to be a semidefinite program (SDP) and transformed into a constrained quadratic programming problem for reducing computational complexity which can be solved by the augmented Lagrange method. The proposed method can significantly improve the performance especially in the scenarios with low signal to noise ratio (SNR), small number of snapshots, and closely spaced correlated sources. In addition, the Cramér-Rao bound (CRB) of the proposed method is developed and the performance guarantee is given according to a version of the restricted isometry property (RIP). The effectiveness and satisfactory performance of the proposed method are illustrated by simulation results. |
| format | Article |
| id | doaj-art-bb685d37b6a34c4e8f1e1032d97008d9 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-bb685d37b6a34c4e8f1e1032d97008d92025-02-03T05:46:47ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/241469241469Augmented Lagrange Based on Modified Covariance Matching Criterion Method for DOA Estimation in Compressed SensingWeijian Si0Xinggen Qu1Lutao Liu2Department of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, ChinaDepartment of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, ChinaDepartment of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, ChinaA novel direction of arrival (DOA) estimation method in compressed sensing (CS) is presented, in which DOA estimation is considered as the joint sparse recovery from multiple measurement vectors (MMV). The proposed method is obtained by minimizing the modified-based covariance matching criterion, which is acquired by adding penalties according to the regularization method. This minimization problem is shown to be a semidefinite program (SDP) and transformed into a constrained quadratic programming problem for reducing computational complexity which can be solved by the augmented Lagrange method. The proposed method can significantly improve the performance especially in the scenarios with low signal to noise ratio (SNR), small number of snapshots, and closely spaced correlated sources. In addition, the Cramér-Rao bound (CRB) of the proposed method is developed and the performance guarantee is given according to a version of the restricted isometry property (RIP). The effectiveness and satisfactory performance of the proposed method are illustrated by simulation results.http://dx.doi.org/10.1155/2014/241469 |
| spellingShingle | Weijian Si Xinggen Qu Lutao Liu Augmented Lagrange Based on Modified Covariance Matching Criterion Method for DOA Estimation in Compressed Sensing The Scientific World Journal |
| title | Augmented Lagrange Based on Modified Covariance Matching Criterion Method for DOA Estimation in Compressed Sensing |
| title_full | Augmented Lagrange Based on Modified Covariance Matching Criterion Method for DOA Estimation in Compressed Sensing |
| title_fullStr | Augmented Lagrange Based on Modified Covariance Matching Criterion Method for DOA Estimation in Compressed Sensing |
| title_full_unstemmed | Augmented Lagrange Based on Modified Covariance Matching Criterion Method for DOA Estimation in Compressed Sensing |
| title_short | Augmented Lagrange Based on Modified Covariance Matching Criterion Method for DOA Estimation in Compressed Sensing |
| title_sort | augmented lagrange based on modified covariance matching criterion method for doa estimation in compressed sensing |
| url | http://dx.doi.org/10.1155/2014/241469 |
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