Joint Data Association, Registration, and Fusion using EM-KF
In performing surveillance using a sensor network, data association and registration are two essential processes which associate data from different sensors and align them in a common coordinate system. While these two processes are usually addressed separately, they actually affect each other. That...
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| Veröffentlicht in: | IEEE transactions on aerospace and electronic systems 2010-04, Vol.46 (2), p.496-507 |
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| container_title | IEEE transactions on aerospace and electronic systems |
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| creator | Zhenhua Li Siyue Chen Leung, Henry Bosse, Eloi |
| description | In performing surveillance using a sensor network, data association and registration are two essential processes which associate data from different sensors and align them in a common coordinate system. While these two processes are usually addressed separately, they actually affect each other. That is, registration requires correctly associated data, and data with sensor biases will result in wrong association. We present a novel joint sensor association, registration, and fusion approach for multisensor surveillance. In order to perform registration and association together, the expectation-maximization (EM) algorithm is incorporated with the Kalman filter (KF) to give simultaneous state and parameter estimates. Computer simulations are carried out to evaluate the performances of the proposed joint association, registration, and fusion method based on EM-KF. |
| doi_str_mv | 10.1109/TAES.2010.5461637 |
| format | Article |
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Computer simulations are carried out to evaluate the performances of the proposed joint association, registration, and fusion method based on EM-KF.</description><subject>Aircraft components</subject><subject>Algorithms</subject><subject>Computer simulation</subject><subject>Coordinate measuring machines</subject><subject>Electronic systems</subject><subject>Estimates</subject><subject>Maximum likelihood estimation</subject><subject>Networks</subject><subject>Parameter estimation</subject><subject>Performance evaluation</subject><subject>Radar tracking</subject><subject>Research and development</subject><subject>Sensor fusion</subject><subject>Sensor systems</subject><subject>Sensors</subject><subject>State estimation</subject><subject>Surveillance</subject><subject>Target tracking</subject><issn>0018-9251</issn><issn>1557-9603</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNp9kE1Lw0AQhhdRsFZ_gHgJeNCD0Z39yOyCl1JbvyqC1vOyTXZLSpvUbHLw37ul1YMHYZiZl3lmYF5CToFeA1B9Mx2M3q8ZjVKKDDKOe6QHUmKqM8r3SY9SUKlmEg7JUQiLKIUSvEdun-qyapM729pkEEKdl7Yt6-oqeXPzMrTNTtmqSMZdiH0SczVPRi_p8_iYHHi7DO5kV_vkYzyaDh_Syev943AwSXPBRJu6GQhKPYoYaIWiBVNaMAsz7zx3zs8KBQigOeq88JxSzUFipjxTvpgx3icX27vrpv7sXGjNqgy5Wy5t5eouGCVlppBrjOTlvyRkCBwRuYzo-R90UXdNFf8wQBkCqkypSMGWyps6hMZ5s27KlW2-ImQ2zpuN82bjvNk5H3fOtjulc-6X_5l-Awhse_I</recordid><startdate>201004</startdate><enddate>201004</enddate><creator>Zhenhua Li</creator><creator>Siyue Chen</creator><creator>Leung, Henry</creator><creator>Bosse, Eloi</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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| source | IEEE Electronic Library (IEL) |
| subjects | Aircraft components Algorithms Computer simulation Coordinate measuring machines Electronic systems Estimates Maximum likelihood estimation Networks Parameter estimation Performance evaluation Radar tracking Research and development Sensor fusion Sensor systems Sensors State estimation Surveillance Target tracking |
| title | Joint Data Association, Registration, and Fusion using EM-KF |
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