DOA Estimation Algorithm for Reconfigurable Intelligent Surface Co-Prime Linear Array Based on Multiple Signal Classification Approach
Co-prime linear arrays (CLAs) provide an additional degree of freedom (DOF) with a limited number of physical sensors, and thus help to improve the resolution of direction of arrival (DOA) estimation algorithms. However, the DOF of traditional CLA is restrained by the structure of the array, which c...
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| Format: | Article |
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MDPI AG
2022-02-01
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| Series: | Information |
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| Online Access: | https://www.mdpi.com/2078-2489/13/2/72 |
| _version_ | 1797479283007946752 |
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| author | Tianyu Lan Kaizhi Huang Liang Jin Xiaoming Xu Xiaoli Sun Zhou Zhong |
| author_facet | Tianyu Lan Kaizhi Huang Liang Jin Xiaoming Xu Xiaoli Sun Zhou Zhong |
| author_sort | Tianyu Lan |
| collection | DOAJ |
| description | Co-prime linear arrays (CLAs) provide an additional degree of freedom (DOF) with a limited number of physical sensors, and thus help to improve the resolution of direction of arrival (DOA) estimation algorithms. However, the DOF of traditional CLA is restrained by the structure of the array, which cannot be adjusted after deployment. In this paper, we propose a DOA estimation algorithm for reconfigurable intelligent surface co-prime linear array (RIS CLA) based on the multiple signal classification approach. Specifically, an RIS CLA is first constructed on the ground of RIS antenna, by turning on/off specific elements at different times. Then, the covariance matrix of the received signal is vectorized, so as to construct a virtual difference array, whose aperture is considerably expanded. Finally, a spectral peak search on the noise subspace of the received signal of the difference array is conducted to obtain the DOA estimation result. Simulations verify the improvement of the proposed algorithm in terms of DOF and resolution. To be specific, the DOF provided by RIS CLA outnumbers that of CLA by more than 30%, and the resolution of the proposed DOA estimation algorithm is effectively improved, with its accuracy increased up to 70% under the low signal-noise-ratio (SNR) scenario, compared with existing algorithms. |
| first_indexed | 2024-03-09T21:43:37Z |
| format | Article |
| id | doaj.art-ee3323566b5d4551b71df4bb9a185cf2 |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-03-09T21:43:37Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
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| spelling | doaj.art-ee3323566b5d4551b71df4bb9a185cf22023-11-23T20:25:23ZengMDPI AGInformation2078-24892022-02-011327210.3390/info13020072DOA Estimation Algorithm for Reconfigurable Intelligent Surface Co-Prime Linear Array Based on Multiple Signal Classification ApproachTianyu Lan0Kaizhi Huang1Liang Jin2Xiaoming Xu3Xiaoli Sun4Zhou Zhong5PLA Strategic Support Force, PLA Information Engineering University, Zhengzhou 450001, ChinaPLA Strategic Support Force, PLA Information Engineering University, Zhengzhou 450001, ChinaPLA Strategic Support Force, PLA Information Engineering University, Zhengzhou 450001, ChinaPLA Strategic Support Force, PLA Information Engineering University, Zhengzhou 450001, ChinaPLA Strategic Support Force, PLA Information Engineering University, Zhengzhou 450001, ChinaPLA Strategic Support Force, PLA Information Engineering University, Zhengzhou 450001, ChinaCo-prime linear arrays (CLAs) provide an additional degree of freedom (DOF) with a limited number of physical sensors, and thus help to improve the resolution of direction of arrival (DOA) estimation algorithms. However, the DOF of traditional CLA is restrained by the structure of the array, which cannot be adjusted after deployment. In this paper, we propose a DOA estimation algorithm for reconfigurable intelligent surface co-prime linear array (RIS CLA) based on the multiple signal classification approach. Specifically, an RIS CLA is first constructed on the ground of RIS antenna, by turning on/off specific elements at different times. Then, the covariance matrix of the received signal is vectorized, so as to construct a virtual difference array, whose aperture is considerably expanded. Finally, a spectral peak search on the noise subspace of the received signal of the difference array is conducted to obtain the DOA estimation result. Simulations verify the improvement of the proposed algorithm in terms of DOF and resolution. To be specific, the DOF provided by RIS CLA outnumbers that of CLA by more than 30%, and the resolution of the proposed DOA estimation algorithm is effectively improved, with its accuracy increased up to 70% under the low signal-noise-ratio (SNR) scenario, compared with existing algorithms.https://www.mdpi.com/2078-2489/13/2/72DOA estimationreconfigurable intelligent surfaceco-prime arraymultiple signal classification |
| spellingShingle | Tianyu Lan Kaizhi Huang Liang Jin Xiaoming Xu Xiaoli Sun Zhou Zhong DOA Estimation Algorithm for Reconfigurable Intelligent Surface Co-Prime Linear Array Based on Multiple Signal Classification Approach Information DOA estimation reconfigurable intelligent surface co-prime array multiple signal classification |
| title | DOA Estimation Algorithm for Reconfigurable Intelligent Surface Co-Prime Linear Array Based on Multiple Signal Classification Approach |
| title_full | DOA Estimation Algorithm for Reconfigurable Intelligent Surface Co-Prime Linear Array Based on Multiple Signal Classification Approach |
| title_fullStr | DOA Estimation Algorithm for Reconfigurable Intelligent Surface Co-Prime Linear Array Based on Multiple Signal Classification Approach |
| title_full_unstemmed | DOA Estimation Algorithm for Reconfigurable Intelligent Surface Co-Prime Linear Array Based on Multiple Signal Classification Approach |
| title_short | DOA Estimation Algorithm for Reconfigurable Intelligent Surface Co-Prime Linear Array Based on Multiple Signal Classification Approach |
| title_sort | doa estimation algorithm for reconfigurable intelligent surface co prime linear array based on multiple signal classification approach |
| topic | DOA estimation reconfigurable intelligent surface co-prime array multiple signal classification |
| url | https://www.mdpi.com/2078-2489/13/2/72 |
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