Passive localisation of mixed near‐field and far‐field signals using the transformed symmetric nested array
Abstract Direction of arrival (DOA) estimation of mixed near‐field (NF) and far‐field (FF) signals is one of the key issues in the study of array signal processing. For more precise localisation performance, sparse arrays have drawn the attention of an increasing number of academics. Excitingly, spa...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-02-01
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| Series: | IET Radar, Sonar & Navigation |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/rsn2.12344 |
| _version_ | 1797905483796840448 |
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| author | Bo Du WeiJia Cui Jianhui Wang Bin Ba Yinsheng Wang |
| author_facet | Bo Du WeiJia Cui Jianhui Wang Bin Ba Yinsheng Wang |
| author_sort | Bo Du |
| collection | DOAJ |
| description | Abstract Direction of arrival (DOA) estimation of mixed near‐field (NF) and far‐field (FF) signals is one of the key issues in the study of array signal processing. For more precise localisation performance, sparse arrays have drawn the attention of an increasing number of academics. Excitingly, sparse arrays enable larger array apertures and higher degrees of freedom (DOFs) than traditionally used uniform linear arrays. Consequently, this study proposes a transformed symmetric nested array (TSNA) for the passive localisation application regarding mixed NF and FF. There are three processes that go into building the proposed array. In the first step, we swap the positions of the uniform linear arrays and the sparse linear arrays in the nested array. In the second step, we place the corresponding array sensors extracted from the uniform linear array behind the uniform linear array to form a new subarray. In the last step, the TSNA is constructed by folding the formed array in half. Furthermore, we give the formula of the largest consecutive lags of the TSNA and its corresponding constructor. Finally, through theoretical analysis and computer performance simulation, this study illustrates the proposed array's numerous advantages over currently used symmetric sparse arrays. |
| first_indexed | 2024-04-10T10:06:03Z |
| format | Article |
| id | doaj.art-c040c3525d504fb0b60a9e69faf1bdbc |
| institution | Directory Open Access Journal |
| issn | 1751-8784 1751-8792 |
| language | English |
| last_indexed | 2024-04-10T10:06:03Z |
| publishDate | 2023-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Radar, Sonar & Navigation |
| spelling | doaj.art-c040c3525d504fb0b60a9e69faf1bdbc2023-02-15T18:03:36ZengWileyIET Radar, Sonar & Navigation1751-87841751-87922023-02-0117233735010.1049/rsn2.12344Passive localisation of mixed near‐field and far‐field signals using the transformed symmetric nested arrayBo Du0WeiJia Cui1Jianhui Wang2Bin Ba3Yinsheng Wang4School of Cyber Science and Engineering Zhengzhou University Zhengzhou ChinaNational Digital Switching System Engineering & Technological Research Center Zhengzhou Henan Province ChinaNational Digital Switching System Engineering & Technological Research Center Zhengzhou Henan Province ChinaNational Digital Switching System Engineering & Technological Research Center Zhengzhou Henan Province ChinaNational Digital Switching System Engineering & Technological Research Center Zhengzhou Henan Province ChinaAbstract Direction of arrival (DOA) estimation of mixed near‐field (NF) and far‐field (FF) signals is one of the key issues in the study of array signal processing. For more precise localisation performance, sparse arrays have drawn the attention of an increasing number of academics. Excitingly, sparse arrays enable larger array apertures and higher degrees of freedom (DOFs) than traditionally used uniform linear arrays. Consequently, this study proposes a transformed symmetric nested array (TSNA) for the passive localisation application regarding mixed NF and FF. There are three processes that go into building the proposed array. In the first step, we swap the positions of the uniform linear arrays and the sparse linear arrays in the nested array. In the second step, we place the corresponding array sensors extracted from the uniform linear array behind the uniform linear array to form a new subarray. In the last step, the TSNA is constructed by folding the formed array in half. Furthermore, we give the formula of the largest consecutive lags of the TSNA and its corresponding constructor. Finally, through theoretical analysis and computer performance simulation, this study illustrates the proposed array's numerous advantages over currently used symmetric sparse arrays.https://doi.org/10.1049/rsn2.12344array signal processingdirection of arrival (DOA) estimationfar‐fieldnear‐fieldtransformed symmetric nested array (TSNA) |
| spellingShingle | Bo Du WeiJia Cui Jianhui Wang Bin Ba Yinsheng Wang Passive localisation of mixed near‐field and far‐field signals using the transformed symmetric nested array IET Radar, Sonar & Navigation array signal processing direction of arrival (DOA) estimation far‐field near‐field transformed symmetric nested array (TSNA) |
| title | Passive localisation of mixed near‐field and far‐field signals using the transformed symmetric nested array |
| title_full | Passive localisation of mixed near‐field and far‐field signals using the transformed symmetric nested array |
| title_fullStr | Passive localisation of mixed near‐field and far‐field signals using the transformed symmetric nested array |
| title_full_unstemmed | Passive localisation of mixed near‐field and far‐field signals using the transformed symmetric nested array |
| title_short | Passive localisation of mixed near‐field and far‐field signals using the transformed symmetric nested array |
| title_sort | passive localisation of mixed near field and far field signals using the transformed symmetric nested array |
| topic | array signal processing direction of arrival (DOA) estimation far‐field near‐field transformed symmetric nested array (TSNA) |
| url | https://doi.org/10.1049/rsn2.12344 |
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