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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/28201

Title: Navigation Integration Using the Fuzzy Strong Tracking Unscented Kalman Filter
Authors: Dah-Jing Jwo;Shih-Yao Lai
Keywords: Integrated navigation;Unscented Kalman filter;Strong tracking filter;Fuzzy logic.
Date: 2009-03-12
Issue Date: 2011-10-21T02:36:12Z
Publisher: The Journal of Navigation
Abstract: abstract:A navigation integration processing scheme, called the strong tracking unscented Kalman filter (STUKF), is based on the combination of an unscented Kalman filter (UKF) and a strong tracking filter (STF). The UKF employs a set of sigma points by deterministic sampling, such that the linearization process is not necessary, and therefore the error caused by linearization as in the traditional extended Kalman filter (EKF) can be avoided. As a type of adaptive filter, the STF is essentially a nonlinear smoother algorithm that employs suboptimal multiple fading factors, in which the softening factors are involved. In order to resolve the shortcoming in traditional approach for selecting the softening factor through personal experience or computer simulation, a novel scheme called the fuzzy strong tracking unscented Kalman filter (FSTUKF) is presented where the Fuzzy Logic Adaptive System (FLAS) is incorporated for determining the softening factor. The proposed FSTUKF algorithm shows promising results in estimation accuracy when applied to the integrated navigation system design, as compared to the EKF, UKF and STUKF approaches.
Relation: 62(2), pp.303-322
URI: http://ntour.ntou.edu.tw/handle/987654321/28201
Appears in Collections:[通訊與導航工程學系] 期刊論文

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