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Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/11780

Title: Applying Neural Network Algorithm to Data Association Technique
Authors: Chung, Yi-Nung;Chen, H.-T.;Juang, D.-J.;Chen, J.-Y.;Lee, J.-R.
Contributors: 電機工程學系
Keywords: Data association;Competitive Hopfield neural network;Kalman filter
Date: 2005-05
Issue Date: 2012-07-02T02:08:27Z
Publisher: IEEE
Abstract: Data association plays an important role in radar tracking algorithm .The problem of tracking multiple targets is studied in this paper. In order to solve the complicated situation and reduce computation burden because of the multiple tracking environment, an approach has been developed in this paper. This algorithm is implemented with an adaptive filter which consists of a data association technique denoted competitive Hopfield
neural network and Kalman filtering to solve both data association and target tracking problems simultaneously. In order to prove the tracking performance, a computer simulation algorithm is proposed in this paper. Because of its computation capability of this algorithm, the radar measurement related to existed target tracks can be chosen optimally. Computer simulation results indicate that this approach
successfully and optimally solves the data association problems.
Relation: IEEE CNNA, 2005年5月28-30日: 114-117
Appears in Collections:[電機工程學系] 會議論文

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