A New Method for Joint Sparse DOA Estimation
To tackle the issue of poor accuracy in single-snapshot data processing for Direction of Arrival (DOA) estimation in passive radar systems, this paper introduces a method for judiciously leveraging multi-snapshot data. This approach effectively enhances the accuracy of DOA estimation and spatial ang...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-11-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/22/7216 |
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| author | Jinyong Hou Changlong Wang Zixuan Zhao Feng Zhou Huaji Zhou |
| author_facet | Jinyong Hou Changlong Wang Zixuan Zhao Feng Zhou Huaji Zhou |
| author_sort | Jinyong Hou |
| collection | DOAJ |
| description | To tackle the issue of poor accuracy in single-snapshot data processing for Direction of Arrival (DOA) estimation in passive radar systems, this paper introduces a method for judiciously leveraging multi-snapshot data. This approach effectively enhances the accuracy of DOA estimation and spatial angle resolution in passive radar systems. Additionally, in response to the non-convex nature of the mixed norm, we propose a hyperbolic tangent model as a replacement, transforming the problem into a directly solvable convex optimization problem. The rationality of this substitution is thoroughly demonstrated. Lastly, through a comparative analysis with existing discrete grid DOA estimation methods, we illustrate the superiority of the proposed approach, particularly under conditions of medium signal-to-noise ratio, varying numbers of snapshots, and close target angles. This method is less affected by the number of array elements, and is more usable in practices verified in real-world scenarios. |
| format | Article |
| id | doaj-art-2a9d3c51f69f40eba0c7caf9f5c3479f |
| institution | Kabale University |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-2a9d3c51f69f40eba0c7caf9f5c3479f2024-11-26T18:21:08ZengMDPI AGSensors1424-82202024-11-012422721610.3390/s24227216A New Method for Joint Sparse DOA EstimationJinyong Hou0Changlong Wang1Zixuan Zhao2Feng Zhou3Huaji Zhou4Key Laboratory of Electronic Information Countermeasure and Simulation Technology, Ministry of Education, Xidian University, Xi’an 710071, ChinaKey Laboratory of Electronic Information Countermeasure and Simulation Technology, Ministry of Education, Xidian University, Xi’an 710071, ChinaKey Laboratory of Electronic Information Countermeasure and Simulation Technology, Ministry of Education, Xidian University, Xi’an 710071, ChinaKey Laboratory of Electronic Information Countermeasure and Simulation Technology, Ministry of Education, Xidian University, Xi’an 710071, ChinaNational Key Laboratory of Electromagnetic Space Security, Jiaxing 314000, ChinaTo tackle the issue of poor accuracy in single-snapshot data processing for Direction of Arrival (DOA) estimation in passive radar systems, this paper introduces a method for judiciously leveraging multi-snapshot data. This approach effectively enhances the accuracy of DOA estimation and spatial angle resolution in passive radar systems. Additionally, in response to the non-convex nature of the mixed norm, we propose a hyperbolic tangent model as a replacement, transforming the problem into a directly solvable convex optimization problem. The rationality of this substitution is thoroughly demonstrated. Lastly, through a comparative analysis with existing discrete grid DOA estimation methods, we illustrate the superiority of the proposed approach, particularly under conditions of medium signal-to-noise ratio, varying numbers of snapshots, and close target angles. This method is less affected by the number of array elements, and is more usable in practices verified in real-world scenarios.https://www.mdpi.com/1424-8220/24/22/7216DOA estimation<i>l<sub>2,th</sub></i> norm minimizationjoint sparse reconstruction |
| spellingShingle | Jinyong Hou Changlong Wang Zixuan Zhao Feng Zhou Huaji Zhou A New Method for Joint Sparse DOA Estimation Sensors DOA estimation <i>l<sub>2,th</sub></i> norm minimization joint sparse reconstruction |
| title | A New Method for Joint Sparse DOA Estimation |
| title_full | A New Method for Joint Sparse DOA Estimation |
| title_fullStr | A New Method for Joint Sparse DOA Estimation |
| title_full_unstemmed | A New Method for Joint Sparse DOA Estimation |
| title_short | A New Method for Joint Sparse DOA Estimation |
| title_sort | new method for joint sparse doa estimation |
| topic | DOA estimation <i>l<sub>2,th</sub></i> norm minimization joint sparse reconstruction |
| url | https://www.mdpi.com/1424-8220/24/22/7216 |
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