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A DOA Estimation Method with High Resolution in the Presence of Satellite Array Error
Compression-sensing-based DOA estimation method can overcome the disadvantages of the traditional spatial spectral estimation algorithm, but the calculation task is heavy and time-consuming, which is limited by the power and processing capability on satellite. At the same time, with the change of th...
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creator | Shi, Wenjun Zhu, Lidong Zhang, Yanggege Chu, Ke He, Ean Shi, Yimai Zhang, Yong He, Wen Liu, Kun |
description | Compression-sensing-based DOA estimation method can overcome the disadvantages of the traditional spatial spectral estimation algorithm, but the calculation task is heavy and time-consuming, which is limited by the power and processing capability on satellite. At the same time, with the change of the space environment and the aging of the devices, the satellite array error problem will appear. Therefore, we proposed a joint subspace decomposition and compressed sensing approximation algorithm to solve the problem of DOA estimation. We first use the Fast Root-MUSIC algorithm to correct the satellite array error and perform a preliminary DOA estimation to reduce the search range of the compressed sensing algorithm, then performed an accurate estimation of the DOA by the L1-svd algorithm. Simulation results show that the proposed algorithm has better performance and less computation complexity under low signal to noise ratio, small fast beat number, as well as in the presence of array error. |
doi_str_mv | 10.1109/ISNCC58260.2023.10323867 |
format | conference_proceeding |
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At the same time, with the change of the space environment and the aging of the devices, the satellite array error problem will appear. Therefore, we proposed a joint subspace decomposition and compressed sensing approximation algorithm to solve the problem of DOA estimation. We first use the Fast Root-MUSIC algorithm to correct the satellite array error and perform a preliminary DOA estimation to reduce the search range of the compressed sensing algorithm, then performed an accurate estimation of the DOA by the L1-svd algorithm. Simulation results show that the proposed algorithm has better performance and less computation complexity under low signal to noise ratio, small fast beat number, as well as in the presence of array error.</description><identifier>EISSN: 2768-0940</identifier><identifier>EISBN: 9798350335590</identifier><identifier>DOI: 10.1109/ISNCC58260.2023.10323867</identifier><language>eng</language><publisher>IEEE</publisher><subject>Approximation algorithms ; array error ; Array signal processing ; compressed sensing ; Direction-of-arrival estimation ; DOA estimation ; Estimation ; high resolution ; Satellite array signal processing ; Satellites ; Signal processing algorithms ; Spatial resolution</subject><ispartof>2023 International Symposium on Networks, Computers and Communications (ISNCC), 2023, p.1-6</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10323867$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,27902,54530,54907</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/10323867$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Shi, Wenjun</creatorcontrib><creatorcontrib>Zhu, Lidong</creatorcontrib><creatorcontrib>Zhang, Yanggege</creatorcontrib><creatorcontrib>Chu, Ke</creatorcontrib><creatorcontrib>He, Ean</creatorcontrib><creatorcontrib>Shi, Yimai</creatorcontrib><creatorcontrib>Zhang, Yong</creatorcontrib><creatorcontrib>He, Wen</creatorcontrib><creatorcontrib>Liu, Kun</creatorcontrib><title>A DOA Estimation Method with High Resolution in the Presence of Satellite Array Error</title><title>2023 International Symposium on Networks, Computers and Communications (ISNCC)</title><addtitle>ISNCC</addtitle><description>Compression-sensing-based DOA estimation method can overcome the disadvantages of the traditional spatial spectral estimation algorithm, but the calculation task is heavy and time-consuming, which is limited by the power and processing capability on satellite. At the same time, with the change of the space environment and the aging of the devices, the satellite array error problem will appear. Therefore, we proposed a joint subspace decomposition and compressed sensing approximation algorithm to solve the problem of DOA estimation. We first use the Fast Root-MUSIC algorithm to correct the satellite array error and perform a preliminary DOA estimation to reduce the search range of the compressed sensing algorithm, then performed an accurate estimation of the DOA by the L1-svd algorithm. Simulation results show that the proposed algorithm has better performance and less computation complexity under low signal to noise ratio, small fast beat number, as well as in the presence of array error.</description><subject>Approximation algorithms</subject><subject>array error</subject><subject>Array signal processing</subject><subject>compressed sensing</subject><subject>Direction-of-arrival estimation</subject><subject>DOA estimation</subject><subject>Estimation</subject><subject>high resolution</subject><subject>Satellite array signal processing</subject><subject>Satellites</subject><subject>Signal processing algorithms</subject><subject>Spatial resolution</subject><issn>2768-0940</issn><isbn>9798350335590</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2023</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo1kF1LwzAYhaMgOOb-gRfvH-h8k7RJc1lqdYPpxLnrEdI3NlJbSSOyf-_w4-pcHHg4z2EMOC45R3Oz3j3WdVEKhUuBQi45SiFLpc_YwmhTygKlLAqD52wmtCozNDlessU0vSGi5FprLmZsX8HttoJmSuHdpjAO8ECpG1v4CqmDVXjt4Jmmsf_86cIAqSN4ijTR4AhGDzubqO9DIqhitEdoYhzjFbvwtp9o8Zdztr9rXupVttner-tqkwXOTcqsV8Zx12ps0XPnKW8tt4p8rq1xuZf2NFwVzuSydMidtSV6ra3yUmhNhZyz619uIKLDRzw5xOPh_wn5DWD8UxY</recordid><startdate>20231023</startdate><enddate>20231023</enddate><creator>Shi, Wenjun</creator><creator>Zhu, Lidong</creator><creator>Zhang, Yanggege</creator><creator>Chu, Ke</creator><creator>He, Ean</creator><creator>Shi, Yimai</creator><creator>Zhang, Yong</creator><creator>He, Wen</creator><creator>Liu, Kun</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>20231023</creationdate><title>A DOA Estimation Method with High Resolution in the Presence of Satellite Array Error</title><author>Shi, Wenjun ; Zhu, Lidong ; Zhang, Yanggege ; Chu, Ke ; He, Ean ; Shi, Yimai ; Zhang, Yong ; He, Wen ; Liu, Kun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i119t-af69c1cd70d0f1cfe4da1a6ef47a9c4f3a76865c9438c01caa80f77a6f3277e53</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Approximation algorithms</topic><topic>array error</topic><topic>Array signal processing</topic><topic>compressed sensing</topic><topic>Direction-of-arrival estimation</topic><topic>DOA estimation</topic><topic>Estimation</topic><topic>high resolution</topic><topic>Satellite array signal processing</topic><topic>Satellites</topic><topic>Signal processing algorithms</topic><topic>Spatial resolution</topic><toplevel>online_resources</toplevel><creatorcontrib>Shi, Wenjun</creatorcontrib><creatorcontrib>Zhu, Lidong</creatorcontrib><creatorcontrib>Zhang, Yanggege</creatorcontrib><creatorcontrib>Chu, Ke</creatorcontrib><creatorcontrib>He, Ean</creatorcontrib><creatorcontrib>Shi, Yimai</creatorcontrib><creatorcontrib>Zhang, Yong</creatorcontrib><creatorcontrib>He, Wen</creatorcontrib><creatorcontrib>Liu, Kun</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Shi, Wenjun</au><au>Zhu, Lidong</au><au>Zhang, Yanggege</au><au>Chu, Ke</au><au>He, Ean</au><au>Shi, Yimai</au><au>Zhang, Yong</au><au>He, Wen</au><au>Liu, Kun</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A DOA Estimation Method with High Resolution in the Presence of Satellite Array Error</atitle><btitle>2023 International Symposium on Networks, Computers and Communications (ISNCC)</btitle><stitle>ISNCC</stitle><date>2023-10-23</date><risdate>2023</risdate><spage>1</spage><epage>6</epage><pages>1-6</pages><eissn>2768-0940</eissn><eisbn>9798350335590</eisbn><abstract>Compression-sensing-based DOA estimation method can overcome the disadvantages of the traditional spatial spectral estimation algorithm, but the calculation task is heavy and time-consuming, which is limited by the power and processing capability on satellite. At the same time, with the change of the space environment and the aging of the devices, the satellite array error problem will appear. Therefore, we proposed a joint subspace decomposition and compressed sensing approximation algorithm to solve the problem of DOA estimation. We first use the Fast Root-MUSIC algorithm to correct the satellite array error and perform a preliminary DOA estimation to reduce the search range of the compressed sensing algorithm, then performed an accurate estimation of the DOA by the L1-svd algorithm. Simulation results show that the proposed algorithm has better performance and less computation complexity under low signal to noise ratio, small fast beat number, as well as in the presence of array error.</abstract><pub>IEEE</pub><doi>10.1109/ISNCC58260.2023.10323867</doi><tpages>6</tpages></addata></record> |
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subjects | Approximation algorithms array error Array signal processing compressed sensing Direction-of-arrival estimation DOA estimation Estimation high resolution Satellite array signal processing Satellites Signal processing algorithms Spatial resolution |
title | A DOA Estimation Method with High Resolution in the Presence of Satellite Array Error |
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