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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/52666

Title: Navigation Performance Enhancement Using IMM Filtering for Time Varying Satellite Signal Quality
Authors: Jen-Hsien Lai
Shu-Ming Chang
Dah-Jing Jwo
Contributors: 國立臺灣海洋大學:電機資訊學院
Date: 2019-05
Issue Date: 2019-12-13T01:37:38Z
Publisher: Scisence Journals
Abstract: Abstract: A novel scheme using fuzzy logic based interacting multiple model (IMM) unscented Kalman filter (UKF) is employed in which the Fuzzy Logic Adaptive System (FLAS) is utilized to address uncertainty of measurement noise, especially for the outlier types of multipath errors for the Global Positioning System (GPS) navigation processing. Multipath is known to be one of the dominant error sources, and multipath mitigation is crucial for improvement of the positioning accuracy. It is not an easy task to establish precise statistical characteristics of measurement noise in practical engineering applications. Based on the filter structural adaptation, the IMM nonlinear filtering provides an alternative for designing the adaptive filter in the GPS navigation processing for time varying satellite signal quality. The uncertainty of the noise can be described by a set of switching models using the multiple model estimation. An UKF employs a set of sigma points by deterministic sampling, which avoids the error caused by linearization as in an extended Kalman filter (EKF). For enhancing further system flexibility, the fuzzy logic system is introduced. The use of IMM with FLAS enables tuning of appropriate values for the measurement noise covariance so as to obtain improved estimation accuracy. Performance assessment will be carried out to show the effectiveness of the proposed approach for positioning improvement in GPS navigation processing.
Relation: 94(4)
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/52666
Appears in Collections:[電機資訊學院] 演講及研討會

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