Location Method of Near Space Radar Network Based on Regularized Constrained Total Least Square: Location Method of Near Space Radar Network Based on Regularized Constrained Total Least Square
The regularized constrained total least square algorithm for near space radar network is discussed in this paper. Firstly the nonlinear equations about range and angle are transformed into linear equations. The influence of error is analyzed by expanding the true range and angle in a first-order Tay...
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Veröffentlicht in: | Dian zi yu xin xi xue bao = Journal of electronics & information technology 2011-07, Vol.33 (7), p.1655-1660 |
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creator | Wang, Shen-shen Feng, Jin-fu Wang, Fang-nian Huang, Feng |
description | The regularized constrained total least square algorithm for near space radar network is discussed in this paper. Firstly the nonlinear equations about range and angle are transformed into linear equations. The influence of error is analyzed by expanding the true range and angle in a first-order Taylor series. Then the location issue is transformed into a regularized constrained total least square issue. The Lagrange function is used to transform the issue into a non-constrained issue. A proper weight is chosen by the least mean square error rule to obtain the location solution. Location accuracy is analyzed. Simulation results show the effectiveness of the algorithm. |
doi_str_mv | 10.3724/SP.J.1146.2010.01211 |
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Simulation results show the effectiveness of the algorithm.</description><subject>Algorithms</subject><subject>Constraints</subject><subject>Electronics</subject><subject>Information systems</subject><subject>Least squares method</subject><subject>Position (location)</subject><subject>Radar networks</subject><subject>Taylor series</subject><issn>1009-5896</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><recordid>eNotkMtOwzAQRbMAiar0D1h4ySbBdmLHXkLFqwqlarq3HHcMgTRu7UQIvh6Xspo7o6MrzUmSK4KzvKTFTb3KFhkhBc8ojjdMKCFnyYRgLFMmJL9IZiF8YIxJTjmXdJKoyhk9tK5HLzC8uy1yFi1Be1TvtQG01tuYlzB8Of-J7nSASPRoDW9jp337E9e568PgddvHvHGD7lAFOgyoPozaw2VybnUXYPY_p8nm4X4zf0qr18fn-W2VGiILkkqCgfBSWiKZwLTBnDUFkEJjAE6LhltGS2FzwzkWTDfSWCYEMMGoNaDzaXJ9qt17dxghDGrXBgNdp3twY1CxO75cCpxHtDihxrsQPFi19-1O-29FsDpaVPVKLdTRojpaVH8W81-c02Z4</recordid><startdate>201107</startdate><enddate>201107</enddate><creator>Wang, Shen-shen</creator><creator>Feng, Jin-fu</creator><creator>Wang, Fang-nian</creator><creator>Huang, Feng</creator><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>H8D</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>201107</creationdate><title>Location Method of Near Space Radar Network Based on Regularized Constrained Total Least Square</title><author>Wang, Shen-shen ; Feng, Jin-fu ; Wang, Fang-nian ; Huang, Feng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1941-910e1679f195802b065b4e14a0ee624b6f5278f3c66085ab9cf588e5852fcea3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>chi ; eng</language><creationdate>2011</creationdate><topic>Algorithms</topic><topic>Constraints</topic><topic>Electronics</topic><topic>Information systems</topic><topic>Least squares method</topic><topic>Position (location)</topic><topic>Radar networks</topic><topic>Taylor series</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Shen-shen</creatorcontrib><creatorcontrib>Feng, Jin-fu</creatorcontrib><creatorcontrib>Wang, Fang-nian</creatorcontrib><creatorcontrib>Huang, Feng</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Dian zi yu xin xi xue bao = Journal of electronics & information technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Shen-shen</au><au>Feng, Jin-fu</au><au>Wang, Fang-nian</au><au>Huang, Feng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Location Method of Near Space Radar Network Based on Regularized Constrained Total Least Square: Location Method of Near Space Radar Network Based on Regularized Constrained Total Least Square</atitle><jtitle>Dian zi yu xin xi xue bao = Journal of electronics & information technology</jtitle><date>2011-07</date><risdate>2011</risdate><volume>33</volume><issue>7</issue><spage>1655</spage><epage>1660</epage><pages>1655-1660</pages><issn>1009-5896</issn><abstract>The regularized constrained total least square algorithm for near space radar network is discussed in this paper. Firstly the nonlinear equations about range and angle are transformed into linear equations. The influence of error is analyzed by expanding the true range and angle in a first-order Taylor series. Then the location issue is transformed into a regularized constrained total least square issue. The Lagrange function is used to transform the issue into a non-constrained issue. A proper weight is chosen by the least mean square error rule to obtain the location solution. Location accuracy is analyzed. Simulation results show the effectiveness of the algorithm.</abstract><doi>10.3724/SP.J.1146.2010.01211</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Constraints Electronics Information systems Least squares method Position (location) Radar networks Taylor series |
title | Location Method of Near Space Radar Network Based on Regularized Constrained Total Least Square: Location Method of Near Space Radar Network Based on Regularized Constrained Total Least Square |
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