DOA estimation using multiple measurement vector model with sparse solutions in linear array scenarios
A novel algorithm is presented based on sparse multiple measurement vector (MMV) model for direction of arrival (DOA) estimation of far-field narrowband sources. The algorithm exploits singular value decomposition denoising to enhance the reconstruction process. The proposed multiple nature of MMV m...
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| Format: | Article |
| Language: | English |
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Springer
2017
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| Online Access: | https://repository.londonmet.ac.uk/1205/1/Open%20Acess.pdf |
| _version_ | 1825624750019313664 |
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| author | Hosseini, Seyyed Moosa Sadeghzadeh, Ramazan Ali Virdee, Bal Singh |
| author_facet | Hosseini, Seyyed Moosa Sadeghzadeh, Ramazan Ali Virdee, Bal Singh |
| author_sort | Hosseini, Seyyed Moosa |
| collection | LMU |
| description | A novel algorithm is presented based on sparse multiple measurement vector (MMV) model for direction of arrival (DOA) estimation of far-field narrowband sources. The algorithm exploits singular value decomposition denoising to enhance the reconstruction process. The proposed multiple nature of MMV model enables the simultaneous processing of several data snapshots to obtain greater accuracy in the DOA estimation. The DOA problem is addressed in both uniform linear array (ULA) and nonuniform linear array (NLA) scenarios. Superior performance is demonstrated in terms of root mean square error and running time of the proposed method when compared with conventional compressed sensing methods such as simultaneous orthogonal matching pursuit (S-OMP), l_2,1 minimization, and root-MUISC. |
| first_indexed | 2024-07-09T03:46:32Z |
| format | Article |
| id | oai:repository.londonmet.ac.uk:1205 |
| institution | London Metropolitan University |
| language | English |
| last_indexed | 2024-07-09T03:46:32Z |
| publishDate | 2017 |
| publisher | Springer |
| record_format | eprints |
| spelling | oai:repository.londonmet.ac.uk:12052017-04-05T07:45:08Z https://repository.londonmet.ac.uk/1205/ DOA estimation using multiple measurement vector model with sparse solutions in linear array scenarios Hosseini, Seyyed Moosa Sadeghzadeh, Ramazan Ali Virdee, Bal Singh 620 Engineering & allied operations A novel algorithm is presented based on sparse multiple measurement vector (MMV) model for direction of arrival (DOA) estimation of far-field narrowband sources. The algorithm exploits singular value decomposition denoising to enhance the reconstruction process. The proposed multiple nature of MMV model enables the simultaneous processing of several data snapshots to obtain greater accuracy in the DOA estimation. The DOA problem is addressed in both uniform linear array (ULA) and nonuniform linear array (NLA) scenarios. Superior performance is demonstrated in terms of root mean square error and running time of the proposed method when compared with conventional compressed sensing methods such as simultaneous orthogonal matching pursuit (S-OMP), l_2,1 minimization, and root-MUISC. Springer 2017-03-28 Article PeerReviewed text en cc_by_nc_nd https://repository.londonmet.ac.uk/1205/1/Open%20Acess.pdf Hosseini, Seyyed Moosa, Sadeghzadeh, Ramazan Ali and Virdee, Bal Singh (2017) DOA estimation using multiple measurement vector model with sparse solutions in linear array scenarios. EURASIP Journal on Wireless Communications and Networking, 58. pp. 1-9. ISSN http://jwcn.eurasipjournals.springeropen.com/articles/10.1186/s13638-017-0838-y http://www.springeropen.com/ 10.1186/s13638-017-0838-y 10.1186/s13638-017-0838-y |
| spellingShingle | 620 Engineering & allied operations Hosseini, Seyyed Moosa Sadeghzadeh, Ramazan Ali Virdee, Bal Singh DOA estimation using multiple measurement vector model with sparse solutions in linear array scenarios |
| title | DOA estimation using multiple measurement vector model with sparse solutions in linear array scenarios |
| title_full | DOA estimation using multiple measurement vector model with sparse solutions in linear array scenarios |
| title_fullStr | DOA estimation using multiple measurement vector model with sparse solutions in linear array scenarios |
| title_full_unstemmed | DOA estimation using multiple measurement vector model with sparse solutions in linear array scenarios |
| title_short | DOA estimation using multiple measurement vector model with sparse solutions in linear array scenarios |
| title_sort | doa estimation using multiple measurement vector model with sparse solutions in linear array scenarios |
| topic | 620 Engineering & allied operations |
| url | https://repository.londonmet.ac.uk/1205/1/Open%20Acess.pdf |
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