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Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/11757

Title: Applying Multiple-Observation Algorithm to Radar Target Tracking Problems
Authors: Hu, Kuo-Chang;Pan, Tien-Szu;Li, Ming-Liang;Chung, Yi-Nung
Contributors: 電機工程學系
Keywords: Multiple maneuvering targets;Multiple-observation algorithm;Multiple-model estimator;Competitive Hopfield neural network(CHNN)
Date: 2009
Issue Date: 2012-07-02T02:07:38Z
Publisher: The Aeronautical and Astronautical Society of the Republic of China
Abstract: An approach of tracking multiple maneuvering targets using the multiple-observation algorithm is developed in this paper. With the developed algorithm, the sensors can be installed in fixed or moving systems which will improve the tracking accuracy and reliability of radar surveillance. Target maneuvering situations are usually existed in radar tracking systems and the maneuvering will cause severe tracking errors. Therefore accurately detecting and estimating maneuvering status of targets is one essential step in the reduction of tracking errors. In this paper, we apply a multiple-model estimator to track maneuvering targets for a radar system. Moreover, in order to achieve the optimal correlation between measurements and the existing targets, a data association using Competitive Hopfield Neural Network (CHNN) technique is applied in this system. Applying the proposed approach, the system will obtain the more accurate tracking results.
Relation: Journal of Aeronautics, Astronautics and Aviation, SeriesA, 41(3): 189-194
Appears in Collections:[電機工程學系] 期刊論文

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