Interference-plus-Noise Covariance Matrix Reconstruction via Spatial Power Spectrum Sampling for Robust Adaptive Beamforming
Recently, a robust adaptive beamforming (RAB) technique based on interference-plus-noise covariance (INC) matrix reconstruction has been proposed, which utilizes the Capon spectrum estimator integrated over a region separated from the direction of the desired signal. Inspired by the sampling and rec...
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| Veröffentlicht in: | IEEE signal processing letters 2016-01, Vol.23 (1), p.121-125 |
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| container_title | IEEE signal processing letters |
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| creator | Zhang, Zhenyu Liu, Wei Leng, Wen Wang, Anguo Shi, Heping |
| description | Recently, a robust adaptive beamforming (RAB) technique based on interference-plus-noise covariance (INC) matrix reconstruction has been proposed, which utilizes the Capon spectrum estimator integrated over a region separated from the direction of the desired signal. Inspired by the sampling and reconstruction idea, in this paper, a novel method named spatial power spectrum sampling (SPSS) is proposed to reconstruct the INC matrix more efficiently, with the corresponding beamforming algorithm developed, where the covariance matrix taper (CMT) technique is employed to further improve its performance. Simulation results are provided to demonstrate the effectiveness of the proposed method. |
| doi_str_mv | 10.1109/LSP.2015.2504954 |
| format | Article |
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Inspired by the sampling and reconstruction idea, in this paper, a novel method named spatial power spectrum sampling (SPSS) is proposed to reconstruct the INC matrix more efficiently, with the corresponding beamforming algorithm developed, where the covariance matrix taper (CMT) technique is employed to further improve its performance. Simulation results are provided to demonstrate the effectiveness of the proposed method.</description><identifier>ISSN: 1070-9908</identifier><identifier>EISSN: 1558-2361</identifier><identifier>DOI: 10.1109/LSP.2015.2504954</identifier><identifier>CODEN: ISPLEM</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Approximation methods ; Array signal processing ; Arrays ; Beamforming ; Computer simulation ; Covariance ; Covariance matrices ; Covariance matrix ; Covariance matrix reconstruction ; Estimators ; Image reconstruction ; matrix taper ; Reconstruction ; robust beamforming ; Robustness ; Sampling ; spatial power spectrum sampling ; Spectral analysis</subject><ispartof>IEEE signal processing letters, 2016-01, Vol.23 (1), p.121-125</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Jan 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c366t-2e68e405ad0881d99b93057d1c653545542ff8081e6b5f8f0be82bc0b33b16003</citedby><cites>FETCH-LOGICAL-c366t-2e68e405ad0881d99b93057d1c653545542ff8081e6b5f8f0be82bc0b33b16003</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/7345553$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/7345553$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Zhang, Zhenyu</creatorcontrib><creatorcontrib>Liu, Wei</creatorcontrib><creatorcontrib>Leng, Wen</creatorcontrib><creatorcontrib>Wang, Anguo</creatorcontrib><creatorcontrib>Shi, Heping</creatorcontrib><title>Interference-plus-Noise Covariance Matrix Reconstruction via Spatial Power Spectrum Sampling for Robust Adaptive Beamforming</title><title>IEEE signal processing letters</title><addtitle>LSP</addtitle><description>Recently, a robust adaptive beamforming (RAB) technique based on interference-plus-noise covariance (INC) matrix reconstruction has been proposed, which utilizes the Capon spectrum estimator integrated over a region separated from the direction of the desired signal. 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Simulation results are provided to demonstrate the effectiveness of the proposed method.</description><subject>Algorithms</subject><subject>Approximation methods</subject><subject>Array signal processing</subject><subject>Arrays</subject><subject>Beamforming</subject><subject>Computer simulation</subject><subject>Covariance</subject><subject>Covariance matrices</subject><subject>Covariance matrix</subject><subject>Covariance matrix reconstruction</subject><subject>Estimators</subject><subject>Image reconstruction</subject><subject>matrix taper</subject><subject>Reconstruction</subject><subject>robust beamforming</subject><subject>Robustness</subject><subject>Sampling</subject><subject>spatial power spectrum sampling</subject><subject>Spectral analysis</subject><issn>1070-9908</issn><issn>1558-2361</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkctPwzAMxisEEuNxR-ISiQuXDidpuvQ4Jh6TxkMMzlWauSiobUqSDpD44wnaxIGT7c8_W7a-JDmhMKYUiovF8nHMgIoxE5AVIttJRlQImTKe092YwwTSogC5nxx4_wYAkkoxSr7nXUBXo8NOY9o3g0_vrfFIZnatnFFRJXcqOPNJnlDbzgc36GBsR9ZGkWWvglENebQf6GKFOrZbslRt35juldTWkSdbDT6Q6Ur1wayRXKJqo97G_lGyV6vG4_E2HiYv11fPs9t08XAzn00XqeZ5HlKGucQMhFqBlHRVFFXBQUxWVOeCi0yIjNW1jA9hXola1lChZJWGivOK5gD8MDnf7O2dfR_Qh7I1XmPTqA7t4Es6KTjLGGU0omf_0Dc7uC5eFykBlHLBWaRgQ2lnvXdYl70zrXJfJYXy144y2lH-2lFu7Ygjp5sRg4h_-ITH8wXnP6ePhuc</recordid><startdate>20160101</startdate><enddate>20160101</enddate><creator>Zhang, Zhenyu</creator><creator>Liu, Wei</creator><creator>Leng, Wen</creator><creator>Wang, Anguo</creator><creator>Shi, Heping</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Inspired by the sampling and reconstruction idea, in this paper, a novel method named spatial power spectrum sampling (SPSS) is proposed to reconstruct the INC matrix more efficiently, with the corresponding beamforming algorithm developed, where the covariance matrix taper (CMT) technique is employed to further improve its performance. Simulation results are provided to demonstrate the effectiveness of the proposed method.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/LSP.2015.2504954</doi><tpages>5</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Algorithms Approximation methods Array signal processing Arrays Beamforming Computer simulation Covariance Covariance matrices Covariance matrix Covariance matrix reconstruction Estimators Image reconstruction matrix taper Reconstruction robust beamforming Robustness Sampling spatial power spectrum sampling Spectral analysis |
| title | Interference-plus-Noise Covariance Matrix Reconstruction via Spatial Power Spectrum Sampling for Robust Adaptive Beamforming |
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