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|Title: ||Applying Image Processing and Neural Network Techniques to Data Association Algorithm|
|Authors: ||Chung, Yi-Nung|
|Keywords: ||Multiple-target tracking;Data association;Competitive Hopeld neural network|
|Issue Date: ||2012-07-02T02:09:50Z
|Publisher: ||Kyushu Tokai University|
|Abstract: ||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.
|Relation: ||International Journal of Innovative Computing, Information and Control, 7(5A): 2427-2439|
|Appears in Collections:||[電機工程學系] 期刊論文|
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