A Joint Doppler Frequency Shift and DOA Estimation Algorithm Based on Sparse Representations for Colocated TDM-MIMO Radar
We address the problem of a new joint Doppler frequency shift (DFS) and direction of arrival (DOA) estimation for colocated TDM-MIMO radar that is a novel technology applied to autocruise and safety driving system in recent years. The signal model of colocated TDM-MIMO radar with few transmitter or...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2014/421391 |
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| author | Tao Chen Huanxin Wu Lutao Liu |
| author_facet | Tao Chen Huanxin Wu Lutao Liu |
| author_sort | Tao Chen |
| collection | DOAJ |
| description | We address the problem of a new joint Doppler frequency shift (DFS) and direction of arrival (DOA) estimation for colocated TDM-MIMO radar that is a novel technology applied to autocruise and safety driving system in recent years. The signal model of colocated TDM-MIMO radar with few transmitter or receiver channels is depicted and “time varying steering vector” model is proved. Inspired by sparse representations theory, we present a new processing scheme for joint DFS and DOA estimation based on the new input signal model of colocated TDM-MIMO radar. An ultracomplete redundancy dictionary for angle-frequency space is founded in order to complete sparse representations of the input signal. The SVD-SR algorithm which stands for joint estimation based on sparse representations using SVD decomposition with OMP algorithm and the improved M-FOCUSS algorithm which combines the classical M-FOCUSS with joint sparse recovery spectrum are applied to the new signal model’s calculation to solve the multiple measurement vectors (MMV) problem. The improved M-FOCUSS algorithm can work more robust than SVD-SR and JS-SR algorithms in the aspects of coherent signals resolution and estimation accuracy. Finally, simulation experiments have shown that the proposed algorithms and schemes are feasible and can be further applied to practical application. |
| format | Article |
| id | doaj-art-d71c7bebe8e34b15852761b7555d7f27 |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-d71c7bebe8e34b15852761b7555d7f272025-02-03T01:11:27ZengWileyJournal of Applied Mathematics1110-757X1687-00422014-01-01201410.1155/2014/421391421391A Joint Doppler Frequency Shift and DOA Estimation Algorithm Based on Sparse Representations for Colocated TDM-MIMO RadarTao Chen0Huanxin Wu1Lutao Liu2College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, ChinaCollege of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, ChinaCollege of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, ChinaWe address the problem of a new joint Doppler frequency shift (DFS) and direction of arrival (DOA) estimation for colocated TDM-MIMO radar that is a novel technology applied to autocruise and safety driving system in recent years. The signal model of colocated TDM-MIMO radar with few transmitter or receiver channels is depicted and “time varying steering vector” model is proved. Inspired by sparse representations theory, we present a new processing scheme for joint DFS and DOA estimation based on the new input signal model of colocated TDM-MIMO radar. An ultracomplete redundancy dictionary for angle-frequency space is founded in order to complete sparse representations of the input signal. The SVD-SR algorithm which stands for joint estimation based on sparse representations using SVD decomposition with OMP algorithm and the improved M-FOCUSS algorithm which combines the classical M-FOCUSS with joint sparse recovery spectrum are applied to the new signal model’s calculation to solve the multiple measurement vectors (MMV) problem. The improved M-FOCUSS algorithm can work more robust than SVD-SR and JS-SR algorithms in the aspects of coherent signals resolution and estimation accuracy. Finally, simulation experiments have shown that the proposed algorithms and schemes are feasible and can be further applied to practical application.http://dx.doi.org/10.1155/2014/421391 |
| spellingShingle | Tao Chen Huanxin Wu Lutao Liu A Joint Doppler Frequency Shift and DOA Estimation Algorithm Based on Sparse Representations for Colocated TDM-MIMO Radar Journal of Applied Mathematics |
| title | A Joint Doppler Frequency Shift and DOA Estimation Algorithm Based on Sparse Representations for Colocated TDM-MIMO Radar |
| title_full | A Joint Doppler Frequency Shift and DOA Estimation Algorithm Based on Sparse Representations for Colocated TDM-MIMO Radar |
| title_fullStr | A Joint Doppler Frequency Shift and DOA Estimation Algorithm Based on Sparse Representations for Colocated TDM-MIMO Radar |
| title_full_unstemmed | A Joint Doppler Frequency Shift and DOA Estimation Algorithm Based on Sparse Representations for Colocated TDM-MIMO Radar |
| title_short | A Joint Doppler Frequency Shift and DOA Estimation Algorithm Based on Sparse Representations for Colocated TDM-MIMO Radar |
| title_sort | joint doppler frequency shift and doa estimation algorithm based on sparse representations for colocated tdm mimo radar |
| url | http://dx.doi.org/10.1155/2014/421391 |
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