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题名: Applying Kalman filter-based fusion algorithm to estimation problems
作者: Lu, Chung-Lain;Chung, Yi-Nung;Lin, Chih-Min;Yu, Chin-Chung;Chen, Tsair-Rong
贡献者: 電機工程學系
关键词: 1-Step conditional maximum likelihood;Adaptive estimator;Kalman filter fusion algorithm
日期: 2010-12
上传时间: 2012-07-02T02:08:57Z
出版者: ICIC Express Letters Office
摘要: An algorithm denoted as Kalman filter-based fusion algorithm for estimation problems is developed in this paper. In this approach, a multiple-sensors data-fusion algorithm is applied. In order to solve the data association and target maneuvering situations, a computational logic, including 1-step conditional maximum likelihood and an adaptive estimator is applied to solve both data association and target maneuvering problems simultaneously. The advantage of this approach is that the multiple sensors can improve the tracking accuracy and the reliability of the radar surveillance. Computer simulation results indicate that this approach can successfully track multiple targets with satisfactory performance.
關聯: ICIC Express Letters, 4(6A): 2109-2114
显示于类别:[電機工程學系] 期刊論文


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