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請使用永久網址來引用或連結此文件:
http://ir.ncue.edu.tw/ir/handle/987654321/11805
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題名: | Applying Image Processing and Neural Network Techniques to Data Association Algorithm |
作者: | Chung, Yi-Nung |
貢獻者: | 電機工程學系 |
關鍵詞: | Multiple-target tracking;Data association;Competitive Hopeld neural network |
日期: | 2011-05
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上傳時間: | 2012-07-02T02:09:50Z
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出版者: | Kyushu Tokai University |
摘要: | Multiple-target tracking (MTT) is a prerequisite step for radar surveillance systems. Data association is the key technique used in radar MTT systems. This paper presents a new approach for data association that uses both quantity data and image information. In order to combine these two attributes, a fusion algorithm based on the competitive Hop eld neural network (CHNN) is developed to match radar measurements with existing target tracks. When target maneuvering problems are detected, an adaptive maneuvering estimator is applied. Computer simulation results indicate that the proposed approach is suitable for multiple-target tracking problems and has good performance. |
關聯: | International Journal of Innovative Computing, Information and Control, 7(5A): 2427-2439 |
顯示於類別: | [電機工程學系] 期刊論文
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