Joint Estimation of Azimuth and Distance for Far-Field Multi Targets Based on Graph Signal Processing
Target position estimation is one of the important research directions in array signal processing. In recent years, the research of target azimuth estimation based on graph signal processing (GSP) has sprung up, which provides new ideas for the Direction of Arrival (DoA) application. In this article...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/5/1110 |
| _version_ | 1797473927984840704 |
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| author | Kefei Liao Zerui Yu Ningbo Xie Junzheng Jiang |
| author_facet | Kefei Liao Zerui Yu Ningbo Xie Junzheng Jiang |
| author_sort | Kefei Liao |
| collection | DOAJ |
| description | Target position estimation is one of the important research directions in array signal processing. In recent years, the research of target azimuth estimation based on graph signal processing (GSP) has sprung up, which provides new ideas for the Direction of Arrival (DoA) application. In this article, by extending GSP-based DOA to joint azimuth and distance estimation and constructing a fully connected graph signal model, a multi-target joint azimuth and distance estimation method based on GSP is proposed. Firstly, the fully connection graph model is established related to the phase information of a linear array. For the fully connection graph, the Fourier transform method is used to solve the estimated response function, and the one-dimensional estimation of azimuth and distance is completed, respectively. Finally, the azimuth and distance estimation information are combined, and the false points in the merging process are removed by using CLEAN algorithm to complete the two-dimensional estimation of targets. The simulation results show that the proposed method has a smaller mean square error than the Multiple Signal Classification (MUSIC) algorithm in azimuth estimation under the condition of a low signal-to-noise ratio and more accurate response values than the MUSIC algorithm in distance estimation under any signal-to-noise ratio in multi-target estimation. |
| first_indexed | 2024-03-09T20:23:07Z |
| format | Article |
| id | doaj.art-36f9eb64b91b454eb86a9542da59fd62 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T20:23:07Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-36f9eb64b91b454eb86a9542da59fd622023-11-23T23:41:36ZengMDPI AGRemote Sensing2072-42922022-02-01145111010.3390/rs14051110Joint Estimation of Azimuth and Distance for Far-Field Multi Targets Based on Graph Signal ProcessingKefei Liao0Zerui Yu1Ningbo Xie2Junzheng Jiang3Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing, School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, ChinaGuangxi Key Laboratory of Wireless Wideband Communication and Signal Processing, School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, ChinaGuangxi Key Laboratory of Wireless Wideband Communication and Signal Processing, School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, ChinaGuangxi Key Laboratory of Wireless Wideband Communication and Signal Processing, School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, ChinaTarget position estimation is one of the important research directions in array signal processing. In recent years, the research of target azimuth estimation based on graph signal processing (GSP) has sprung up, which provides new ideas for the Direction of Arrival (DoA) application. In this article, by extending GSP-based DOA to joint azimuth and distance estimation and constructing a fully connected graph signal model, a multi-target joint azimuth and distance estimation method based on GSP is proposed. Firstly, the fully connection graph model is established related to the phase information of a linear array. For the fully connection graph, the Fourier transform method is used to solve the estimated response function, and the one-dimensional estimation of azimuth and distance is completed, respectively. Finally, the azimuth and distance estimation information are combined, and the false points in the merging process are removed by using CLEAN algorithm to complete the two-dimensional estimation of targets. The simulation results show that the proposed method has a smaller mean square error than the Multiple Signal Classification (MUSIC) algorithm in azimuth estimation under the condition of a low signal-to-noise ratio and more accurate response values than the MUSIC algorithm in distance estimation under any signal-to-noise ratio in multi-target estimation.https://www.mdpi.com/2072-4292/14/5/1110direction of arrivalgraph signal processingarray signal processinggraph Fourier transformjoint estimation |
| spellingShingle | Kefei Liao Zerui Yu Ningbo Xie Junzheng Jiang Joint Estimation of Azimuth and Distance for Far-Field Multi Targets Based on Graph Signal Processing Remote Sensing direction of arrival graph signal processing array signal processing graph Fourier transform joint estimation |
| title | Joint Estimation of Azimuth and Distance for Far-Field Multi Targets Based on Graph Signal Processing |
| title_full | Joint Estimation of Azimuth and Distance for Far-Field Multi Targets Based on Graph Signal Processing |
| title_fullStr | Joint Estimation of Azimuth and Distance for Far-Field Multi Targets Based on Graph Signal Processing |
| title_full_unstemmed | Joint Estimation of Azimuth and Distance for Far-Field Multi Targets Based on Graph Signal Processing |
| title_short | Joint Estimation of Azimuth and Distance for Far-Field Multi Targets Based on Graph Signal Processing |
| title_sort | joint estimation of azimuth and distance for far field multi targets based on graph signal processing |
| topic | direction of arrival graph signal processing array signal processing graph Fourier transform joint estimation |
| url | https://www.mdpi.com/2072-4292/14/5/1110 |
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