A track correlation algorithm for multi-sensor integration
A track correlation algorithm in a multi-sensor integration system for a surveillance mission is proposed. The performance of such track correlation processing is strongly dependent not only on the target state estimation error distribution but also on the target spatial density distribution. Theref...
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| Veröffentlicht in: | Journal of guidance, control, and dynamics control, and dynamics, 1987-03, Vol.10 (2), p.166-171 |
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| container_end_page | 171 |
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| container_issue | 2 |
| container_start_page | 166 |
| container_title | Journal of guidance, control, and dynamics |
| container_volume | 10 |
| creator | KOSAKA, MICHITAKA MIYAMOTO, SHOJI IHARA, HIROKAZU |
| description | A track correlation algorithm in a multi-sensor integration system for a surveillance mission is proposed. The performance of such track correlation processing is strongly dependent not only on the target state estimation error distribution but also on the target spatial density distribution. Therefore, a track correlation problem is formulated as the likelihood ratio test problem which can take both target state estimation error distribution and target state spatial density distribution into consideration. From this formulation, the correlation algorithm for on-line processing is derived by modifications and approximations. Through analytical evaluations and simulation studies, it is shown that the proposed algorithm, is superior to the conventional nearest neighbor algorithm. |
| doi_str_mv | 10.2514/3.20198 |
| format | Article |
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The performance of such track correlation processing is strongly dependent not only on the target state estimation error distribution but also on the target spatial density distribution. Therefore, a track correlation problem is formulated as the likelihood ratio test problem which can take both target state estimation error distribution and target state spatial density distribution into consideration. From this formulation, the correlation algorithm for on-line processing is derived by modifications and approximations. Through analytical evaluations and simulation studies, it is shown that the proposed algorithm, is superior to the conventional nearest neighbor algorithm.</description><subject>Aircraft</subject><subject>Algorithms</subject><subject>Approximation</subject><subject>Hypotheses</subject><subject>Laboratories</subject><subject>Optimization techniques</subject><subject>Sensors</subject><subject>Surveillance</subject><subject>Systems development</subject><issn>0731-5090</issn><issn>1533-3884</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1987</creationdate><recordtype>article</recordtype><recordid>eNqN0E1LAzEQBuAgCtYq_oUFRfGwNR-b7MZbKX5BwYueQ5JN6tZ0U5Ms6L83toJQPHgahnl4mRkAThGcYIqqazLBEPFmD4wQJaQkTVPtgxGsCSop5PAQHMW4hBARhuoRuJkWKUj9VmgfgnEydb4vpFv40KXXVWF9KFaDS10ZTR9z0_XJLMKGHYMDK100Jz91DF7ubp9nD-X86f5xNp2XktA6lY1lSpMGEU0rRGpEVFthjQhWlKmaWWYVVkxZ3VKuEbIcas14a2mlLGusImNwsc1dB_8-mJjEqovaOCd744cocFUzwvOt_4K04hme7cClH0KfjxCY5B05plmOweVW6eBjDMaKdehWMnwKBMX3qwURm1dnebWVspPyN-tnLNatFXZwLpmPlO35X3Y38guLW4lM</recordid><startdate>19870301</startdate><enddate>19870301</enddate><creator>KOSAKA, MICHITAKA</creator><creator>MIYAMOTO, SHOJI</creator><creator>IHARA, HIROKAZU</creator><general>American Institute of Aeronautics and Astronautics</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>19870301</creationdate><title>A track correlation algorithm for multi-sensor integration</title><author>KOSAKA, MICHITAKA ; MIYAMOTO, SHOJI ; IHARA, HIROKAZU</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a357t-8f6bc3813c5413713bd42c132b56b76f6fb2b6bfcd59c11f90cc69df54bf68fb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1987</creationdate><topic>Aircraft</topic><topic>Algorithms</topic><topic>Approximation</topic><topic>Hypotheses</topic><topic>Laboratories</topic><topic>Optimization techniques</topic><topic>Sensors</topic><topic>Surveillance</topic><topic>Systems development</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>KOSAKA, MICHITAKA</creatorcontrib><creatorcontrib>MIYAMOTO, SHOJI</creatorcontrib><creatorcontrib>IHARA, HIROKAZU</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering 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>Journal of guidance, control, and dynamics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>KOSAKA, MICHITAKA</au><au>MIYAMOTO, SHOJI</au><au>IHARA, HIROKAZU</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A track correlation algorithm for multi-sensor integration</atitle><jtitle>Journal of guidance, control, and dynamics</jtitle><date>1987-03-01</date><risdate>1987</risdate><volume>10</volume><issue>2</issue><spage>166</spage><epage>171</epage><pages>166-171</pages><issn>0731-5090</issn><eissn>1533-3884</eissn><abstract>A track correlation algorithm in a multi-sensor integration system for a surveillance mission is proposed. The performance of such track correlation processing is strongly dependent not only on the target state estimation error distribution but also on the target spatial density distribution. Therefore, a track correlation problem is formulated as the likelihood ratio test problem which can take both target state estimation error distribution and target state spatial density distribution into consideration. From this formulation, the correlation algorithm for on-line processing is derived by modifications and approximations. Through analytical evaluations and simulation studies, it is shown that the proposed algorithm, is superior to the conventional nearest neighbor algorithm.</abstract><cop>Reston</cop><pub>American Institute of Aeronautics and Astronautics</pub><doi>10.2514/3.20198</doi><tpages>6</tpages></addata></record> |
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| ispartof | Journal of guidance, control, and dynamics, 1987-03, Vol.10 (2), p.166-171 |
| issn | 0731-5090 1533-3884 |
| language | eng |
| recordid | cdi_aiaa_journals_3_20198_pdf_fulltext |
| source | Alma/SFX Local Collection |
| subjects | Aircraft Algorithms Approximation Hypotheses Laboratories Optimization techniques Sensors Surveillance Systems development |
| title | A track correlation algorithm for multi-sensor integration |
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