An Improved MUSIC Algorithm Implemented with High-speed Parallel Optimization for FPGA
This paper proposes an improved MUSIC algorithm with high-speed parallel optimization for FPGA. Although MUSIC algorithm is a high-performance, classic DOA method, it needs estimation and eigenstructure decomposition of covariance matrix, which is time-consuming with high computation cost and not su...
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| creator | Zhou Zou Wang Hongyuan Yu Guowen |
| description | This paper proposes an improved MUSIC algorithm with high-speed parallel optimization for FPGA. Although MUSIC algorithm is a high-performance, classic DOA method, it needs estimation and eigenstructure decomposition of covariance matrix, which is time-consuming with high computation cost and not suitable for FPGA implementations. In this paper, the authors present an optimization algorithm without the eigenstructure decomposition of the covariance matrix. This algorithm offers far lower computation cost compared to MUSIC at the expense of little performance decrease. With parallel preprocessing focusing on correlation matrices estimation and spectral peak search, an FPGA implementation is introduced, and proved to be efficient through theoretical analysis, simulation and hardware implementation. |
| doi_str_mv | 10.1109/ISAPE.2006.353475 |
| format | Conference Proceeding |
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Although MUSIC algorithm is a high-performance, classic DOA method, it needs estimation and eigenstructure decomposition of covariance matrix, which is time-consuming with high computation cost and not suitable for FPGA implementations. In this paper, the authors present an optimization algorithm without the eigenstructure decomposition of the covariance matrix. This algorithm offers far lower computation cost compared to MUSIC at the expense of little performance decrease. With parallel preprocessing focusing on correlation matrices estimation and spectral peak search, an FPGA implementation is introduced, and proved to be efficient through theoretical analysis, simulation and hardware implementation.</description><identifier>ISBN: 1424401623</identifier><identifier>ISBN: 9781424401628</identifier><identifier>EISBN: 9781424401635</identifier><identifier>EISBN: 1424401631</identifier><identifier>DOI: 10.1109/ISAPE.2006.353475</identifier><language>eng</language><publisher>IEEE</publisher><subject>Additive white noise ; Algorithm design and analysis ; Computational efficiency ; Covariance matrix ; Direction of arrival estimation ; DOA Estimation ; Field programmable gate arrays ; FPGA Implementation ; Gaussian noise ; Hardware ; High-Speed Parallel Optimization ; Matrix decomposition ; Multiple signal classification ; MUSIC</subject><ispartof>2006 7th International Symposium on Antennas, Propagation & EM Theory, 2006, p.1-4</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/4168136$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/4168136$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Zhou Zou</creatorcontrib><creatorcontrib>Wang Hongyuan</creatorcontrib><creatorcontrib>Yu Guowen</creatorcontrib><title>An Improved MUSIC Algorithm Implemented with High-speed Parallel Optimization for FPGA</title><title>2006 7th International Symposium on Antennas, Propagation & EM Theory</title><addtitle>ISAPE</addtitle><description>This paper proposes an improved MUSIC algorithm with high-speed parallel optimization for FPGA. Although MUSIC algorithm is a high-performance, classic DOA method, it needs estimation and eigenstructure decomposition of covariance matrix, which is time-consuming with high computation cost and not suitable for FPGA implementations. In this paper, the authors present an optimization algorithm without the eigenstructure decomposition of the covariance matrix. This algorithm offers far lower computation cost compared to MUSIC at the expense of little performance decrease. With parallel preprocessing focusing on correlation matrices estimation and spectral peak search, an FPGA implementation is introduced, and proved to be efficient through theoretical analysis, simulation and hardware implementation.</description><subject>Additive white noise</subject><subject>Algorithm design and analysis</subject><subject>Computational efficiency</subject><subject>Covariance matrix</subject><subject>Direction of arrival estimation</subject><subject>DOA Estimation</subject><subject>Field programmable gate arrays</subject><subject>FPGA Implementation</subject><subject>Gaussian noise</subject><subject>Hardware</subject><subject>High-Speed Parallel Optimization</subject><subject>Matrix decomposition</subject><subject>Multiple signal classification</subject><subject>MUSIC</subject><isbn>1424401623</isbn><isbn>9781424401628</isbn><isbn>9781424401635</isbn><isbn>1424401631</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2006</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNp9iV0LgjAYRhcR9OUPiG72B7LNzamXIn14EQlWtzHorRabypSifn0Gddtz83DOQWhCiUspieZpHmcL1yNEuMxnPPA7yImCkHKPc0IF87to-AOP9ZFT1zfSjkVM0HCADnGBU1PZ8g4nvNnnaYJjfSmtaq7mEzQYKJq2PVqD1-pyndUVtJxJK7UGjbdVo4x6yUaVBT6XFi-zVTxGvbPUNTjfH6HpcrFL1jMFAMfKKiPt88ipCCkT7H99A2_VQn0</recordid><startdate>200610</startdate><enddate>200610</enddate><creator>Zhou Zou</creator><creator>Wang Hongyuan</creator><creator>Yu Guowen</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200610</creationdate><title>An Improved MUSIC Algorithm Implemented with High-speed Parallel Optimization for FPGA</title><author>Zhou Zou ; Wang Hongyuan ; Yu Guowen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-ieee_primary_41681363</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Additive white noise</topic><topic>Algorithm design and analysis</topic><topic>Computational efficiency</topic><topic>Covariance matrix</topic><topic>Direction of arrival estimation</topic><topic>DOA Estimation</topic><topic>Field programmable gate arrays</topic><topic>FPGA Implementation</topic><topic>Gaussian noise</topic><topic>Hardware</topic><topic>High-Speed Parallel Optimization</topic><topic>Matrix decomposition</topic><topic>Multiple signal classification</topic><topic>MUSIC</topic><toplevel>online_resources</toplevel><creatorcontrib>Zhou Zou</creatorcontrib><creatorcontrib>Wang Hongyuan</creatorcontrib><creatorcontrib>Yu Guowen</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>Zhou Zou</au><au>Wang Hongyuan</au><au>Yu Guowen</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>An Improved MUSIC Algorithm Implemented with High-speed Parallel Optimization for FPGA</atitle><btitle>2006 7th International Symposium on Antennas, Propagation & EM Theory</btitle><stitle>ISAPE</stitle><date>2006-10</date><risdate>2006</risdate><spage>1</spage><epage>4</epage><pages>1-4</pages><isbn>1424401623</isbn><isbn>9781424401628</isbn><eisbn>9781424401635</eisbn><eisbn>1424401631</eisbn><abstract>This paper proposes an improved MUSIC algorithm with high-speed parallel optimization for FPGA. Although MUSIC algorithm is a high-performance, classic DOA method, it needs estimation and eigenstructure decomposition of covariance matrix, which is time-consuming with high computation cost and not suitable for FPGA implementations. In this paper, the authors present an optimization algorithm without the eigenstructure decomposition of the covariance matrix. This algorithm offers far lower computation cost compared to MUSIC at the expense of little performance decrease. With parallel preprocessing focusing on correlation matrices estimation and spectral peak search, an FPGA implementation is introduced, and proved to be efficient through theoretical analysis, simulation and hardware implementation.</abstract><pub>IEEE</pub><doi>10.1109/ISAPE.2006.353475</doi></addata></record> |
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| ispartof | 2006 7th International Symposium on Antennas, Propagation & EM Theory, 2006, p.1-4 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Additive white noise Algorithm design and analysis Computational efficiency Covariance matrix Direction of arrival estimation DOA Estimation Field programmable gate arrays FPGA Implementation Gaussian noise Hardware High-Speed Parallel Optimization Matrix decomposition Multiple signal classification MUSIC |
| title | An Improved MUSIC Algorithm Implemented with High-speed Parallel Optimization for FPGA |
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