Compressed Sensing in On-Grid MIMO Radar
The accurate detection of targets is a significant problem in multiple-input multiple-output (MIMO) radar. Recent advances of Compressive Sensing offer a means of efficiently accomplishing this task. The sparsity constraints needed to apply the techniques of Compressive Sensing to problems in radar...
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2015/397878 |
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| author | Michael F. Minner |
| author_facet | Michael F. Minner |
| author_sort | Michael F. Minner |
| collection | DOAJ |
| description | The accurate detection of targets is a significant problem in multiple-input multiple-output (MIMO) radar. Recent advances of Compressive Sensing offer a means of efficiently accomplishing this task. The sparsity constraints needed to apply the techniques of Compressive Sensing to problems in radar systems have led to discretizations of the target scene in various domains, such as azimuth, time delay, and Doppler. Building upon recent work, we investigate the feasibility of on-grid Compressive Sensing-based MIMO radar via a threefold azimuth-delay-Doppler discretization for target detection and parameter estimation. We utilize a colocated random sensor array and transmit distinct linear chirps to a small scene with few, slowly moving targets. Relying upon standard far-field and narrowband assumptions, we analyze the efficacy of various recovery algorithms in determining the parameters of the scene through numerical simulations, with particular focus on the l1-squared Nonnegative Regularization method. |
| format | Article |
| id | doaj-art-606f3ad64b484cd6b1ca8e3eaa87012f |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-606f3ad64b484cd6b1ca8e3eaa87012f2025-02-03T01:31:27ZengWileyThe Scientific World Journal2356-61401537-744X2015-01-01201510.1155/2015/397878397878Compressed Sensing in On-Grid MIMO RadarMichael F. Minner0Department of Mathematics, Drexel University, Philadelphia, PA 19104-0250, USAThe accurate detection of targets is a significant problem in multiple-input multiple-output (MIMO) radar. Recent advances of Compressive Sensing offer a means of efficiently accomplishing this task. The sparsity constraints needed to apply the techniques of Compressive Sensing to problems in radar systems have led to discretizations of the target scene in various domains, such as azimuth, time delay, and Doppler. Building upon recent work, we investigate the feasibility of on-grid Compressive Sensing-based MIMO radar via a threefold azimuth-delay-Doppler discretization for target detection and parameter estimation. We utilize a colocated random sensor array and transmit distinct linear chirps to a small scene with few, slowly moving targets. Relying upon standard far-field and narrowband assumptions, we analyze the efficacy of various recovery algorithms in determining the parameters of the scene through numerical simulations, with particular focus on the l1-squared Nonnegative Regularization method.http://dx.doi.org/10.1155/2015/397878 |
| spellingShingle | Michael F. Minner Compressed Sensing in On-Grid MIMO Radar The Scientific World Journal |
| title | Compressed Sensing in On-Grid MIMO Radar |
| title_full | Compressed Sensing in On-Grid MIMO Radar |
| title_fullStr | Compressed Sensing in On-Grid MIMO Radar |
| title_full_unstemmed | Compressed Sensing in On-Grid MIMO Radar |
| title_short | Compressed Sensing in On-Grid MIMO Radar |
| title_sort | compressed sensing in on grid mimo radar |
| url | http://dx.doi.org/10.1155/2015/397878 |
| work_keys_str_mv | AT michaelfminner compressedsensinginongridmimoradar |