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題名: | Mulitple-Target Tracking with Competitive Hopfield Neural Network-based Data Association |
作者: | Chung, Yi-Nung;Chou, Pao-Hua;Yang, Maw-Rong;Chen, Hsin-Ta |
貢獻者: | 電機工程學系 |
日期: | 2007-07
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上傳時間: | 2012-07-02T02:06:51Z
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出版者: | IEEE |
摘要: | Data association which obtains relationship between radar measurements and existing tracks plays one important role in radar multiple-target tracking (MTT) systems. A new approach to data association based on the competitive Hopfield neural network (CHNN) is investigated, where the matching between radar measurements and existing target tracks is used as a criterion to achieve a global consideration. Embedded within the CHNN is a competitive learning algorithm that resolves the dilemma of occasional irrational solutions in traditional Hopfield neural networks. Additionally, it is also shown that our proposed CHNN-based network is guaranteed to converge to a stable state in performing data association and the CHNN-based data association combined with an MTT system demonstrates target tracking capability. Computer simulation results indicate that this approach successfully solves the data association problems. |
關聯: | IEEE Trans. Aerosp.Electron. Syst, 43(3): 1180-1188 |
顯示於類別: | [電機工程學系] 期刊論文
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