DOA Estimation and Self-Calibration under Unknown Mutual Coupling
In practical applications, the assumption of omnidirectional elements is not effective in general, which leads to the direction-dependent mutual coupling (MC). Under this condition, the performance of traditional calibration algorithms suffers. This paper proposes a new self-calibration method based...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/19/4/978 |
| _version_ | 1818001380164501504 |
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| author | Dong Qi Min Tang Shiwen Chen Zhixin Liu Yongjun Zhao |
| author_facet | Dong Qi Min Tang Shiwen Chen Zhixin Liu Yongjun Zhao |
| author_sort | Dong Qi |
| collection | DOAJ |
| description | In practical applications, the assumption of omnidirectional elements is not effective in general, which leads to the direction-dependent mutual coupling (MC). Under this condition, the performance of traditional calibration algorithms suffers. This paper proposes a new self-calibration method based on the time-frequency distributions (TFDs) in the presence of direction-dependent MC. Firstly, the time-frequency (TF) transformation is used to calculate the space-time-frequency distributions (STFDs) matrix of received signals. After that, the estimated steering vector and corresponding noise subspace are estimated by the steps of noise removing, single-source TF points extracting and clustering. Then according to the transformation relationship between the MC coefficients, steering vector and MC matrix, we deduce a set of linear equations. Finally, with two-step alternating iteration, the equations are solved by least square method in order to estimate DOA and MC coefficients. Simulations results show that the proposed algorithm can achieve direction-dependent MC self-calibration and outperforms the existing algorithms. |
| first_indexed | 2024-04-14T03:33:44Z |
| format | Article |
| id | doaj.art-51bb21f9fa6c495da68d4940b68070f1 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T03:33:44Z |
| publishDate | 2019-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-51bb21f9fa6c495da68d4940b68070f12022-12-22T02:14:52ZengMDPI AGSensors1424-82202019-02-0119497810.3390/s19040978s19040978DOA Estimation and Self-Calibration under Unknown Mutual CouplingDong QiMin Tang0Shiwen Chen1Zhixin Liu2Yongjun Zhao3National Digital Switching System Engineering and Technological Research Center (NDSC), Zhengzhou 86-450001, ChinaNational Digital Switching System Engineering and Technological Research Center (NDSC), Zhengzhou 86-450001, ChinaNational Digital Switching System Engineering and Technological Research Center (NDSC), Zhengzhou 86-450001, ChinaNational Digital Switching System Engineering and Technological Research Center (NDSC), Zhengzhou 86-450001, ChinaIn practical applications, the assumption of omnidirectional elements is not effective in general, which leads to the direction-dependent mutual coupling (MC). Under this condition, the performance of traditional calibration algorithms suffers. This paper proposes a new self-calibration method based on the time-frequency distributions (TFDs) in the presence of direction-dependent MC. Firstly, the time-frequency (TF) transformation is used to calculate the space-time-frequency distributions (STFDs) matrix of received signals. After that, the estimated steering vector and corresponding noise subspace are estimated by the steps of noise removing, single-source TF points extracting and clustering. Then according to the transformation relationship between the MC coefficients, steering vector and MC matrix, we deduce a set of linear equations. Finally, with two-step alternating iteration, the equations are solved by least square method in order to estimate DOA and MC coefficients. Simulations results show that the proposed algorithm can achieve direction-dependent MC self-calibration and outperforms the existing algorithms.https://www.mdpi.com/1424-8220/19/4/978DOA estimationdirection-dependent mutual couplingtime-frequency distributionself-calibration |
| spellingShingle | Dong Qi Min Tang Shiwen Chen Zhixin Liu Yongjun Zhao DOA Estimation and Self-Calibration under Unknown Mutual Coupling Sensors DOA estimation direction-dependent mutual coupling time-frequency distribution self-calibration |
| title | DOA Estimation and Self-Calibration under Unknown Mutual Coupling |
| title_full | DOA Estimation and Self-Calibration under Unknown Mutual Coupling |
| title_fullStr | DOA Estimation and Self-Calibration under Unknown Mutual Coupling |
| title_full_unstemmed | DOA Estimation and Self-Calibration under Unknown Mutual Coupling |
| title_short | DOA Estimation and Self-Calibration under Unknown Mutual Coupling |
| title_sort | doa estimation and self calibration under unknown mutual coupling |
| topic | DOA estimation direction-dependent mutual coupling time-frequency distribution self-calibration |
| url | https://www.mdpi.com/1424-8220/19/4/978 |
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