Multiple input multiple output radar imaging based on multidimensional linear equations and sparse signal recovery
Multiple input multiple output (MIMO) radar forms large virtual aperture and improves the cross-range resolution of radar imaging. Sparse signal recovery algorithms can be used to improve image quality of target with sparse property in spatial domain. Conventional sparse signal recovery-based MIMO r...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
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2018
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| Online Access: | https://hdl.handle.net/10356/87738 http://hdl.handle.net/10220/45479 |
| _version_ | 1811683571673333760 |
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| author | Ma, Changzheng Yeo, Tat Soon Ng, Boon Poh |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Ma, Changzheng Yeo, Tat Soon Ng, Boon Poh |
| author_sort | Ma, Changzheng |
| collection | NTU |
| description | Multiple input multiple output (MIMO) radar forms large virtual aperture and improves the cross-range resolution of radar imaging. Sparse signal recovery algorithms can be used to improve image quality of target with sparse property in spatial domain. Conventional sparse signal recovery-based MIMO radar imaging method rearranges the received two-dimensional (2D) or 3D signals into a vector, then linear equations describing the relation between the received signal and the reflectivity of the scatterers are solved. However, this method occupies huge memory spaces and increases the computational load. In this study, by introducing synthetic codes, multidimensional linear equations of MIMO radar imaging are derived, which occupy less memory spaces and cost less computationally. A L1 L0 norms homotopy sparse signal recovery algorithm for multidimensional linear equations is used to recover the image. Simulation results verify the high efficiency of using multidimensional linear equations. |
| first_indexed | 2024-10-01T04:14:51Z |
| format | Journal Article |
| id | ntu-10356/87738 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:14:51Z |
| publishDate | 2018 |
| record_format | dspace |
| spelling | ntu-10356/877382020-03-07T14:02:34Z Multiple input multiple output radar imaging based on multidimensional linear equations and sparse signal recovery Ma, Changzheng Yeo, Tat Soon Ng, Boon Poh School of Electrical and Electronic Engineering Multidimensional Linear Equations MIMO Radar Multiple input multiple output (MIMO) radar forms large virtual aperture and improves the cross-range resolution of radar imaging. Sparse signal recovery algorithms can be used to improve image quality of target with sparse property in spatial domain. Conventional sparse signal recovery-based MIMO radar imaging method rearranges the received two-dimensional (2D) or 3D signals into a vector, then linear equations describing the relation between the received signal and the reflectivity of the scatterers are solved. However, this method occupies huge memory spaces and increases the computational load. In this study, by introducing synthetic codes, multidimensional linear equations of MIMO radar imaging are derived, which occupy less memory spaces and cost less computationally. A L1 L0 norms homotopy sparse signal recovery algorithm for multidimensional linear equations is used to recover the image. Simulation results verify the high efficiency of using multidimensional linear equations. MOE (Min. of Education, S’pore) Published version 2018-08-06T07:39:52Z 2019-12-06T16:48:22Z 2018-08-06T07:39:52Z 2019-12-06T16:48:22Z 2018 Journal Article Ma, C., Yeo, T. S., & Ng, B. P. (2018). Multiple input multiple output radar imaging based on multidimensional linear equations and sparse signal recovery. IET Radar, Sonar & Navigation, 12(1), 3-10. 1751-8784 https://hdl.handle.net/10356/87738 http://hdl.handle.net/10220/45479 10.1049/iet-rsn.2017.0149 en IET Radar, Sonar & Navigation © 2017 Institution of Engineering and Technology. This paper was published in IET Radar, Sonar & Navigation and is made available as an electronic reprint (preprint) with permission of Institution of Engineering and Technology. The published version is available at: [http://dx.doi.org/10.1049/iet-rsn.2017.0149]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. 8 p. application/pdf |
| spellingShingle | Multidimensional Linear Equations MIMO Radar Ma, Changzheng Yeo, Tat Soon Ng, Boon Poh Multiple input multiple output radar imaging based on multidimensional linear equations and sparse signal recovery |
| title | Multiple input multiple output radar imaging based on multidimensional linear equations and sparse signal recovery |
| title_full | Multiple input multiple output radar imaging based on multidimensional linear equations and sparse signal recovery |
| title_fullStr | Multiple input multiple output radar imaging based on multidimensional linear equations and sparse signal recovery |
| title_full_unstemmed | Multiple input multiple output radar imaging based on multidimensional linear equations and sparse signal recovery |
| title_short | Multiple input multiple output radar imaging based on multidimensional linear equations and sparse signal recovery |
| title_sort | multiple input multiple output radar imaging based on multidimensional linear equations and sparse signal recovery |
| topic | Multidimensional Linear Equations MIMO Radar |
| url | https://hdl.handle.net/10356/87738 http://hdl.handle.net/10220/45479 |
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