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Vol. 6, Special Issue, August 2009, pp.4-17





GPS Navigation Processing Using the IMM-Based Extended Kalman Filter


Dah-Jing JWO, Chien-Hao TSENG

Department of Communications, Navigation and Control Engineering

National Taiwan Ocean University

2 Pei-Ning Rd., Keelung 202-24, Taiwan

Tel: +886-2-24622192 ext. 7209, fax: +886-2-24633492

E-mail: djjwo@mail.ntou.edu.tw



Received: 10 July 2009   /Accepted: 31 July 2009   /Published: 10 August 2009


Abstract: This paper presents an interacting multiple model (IMM)-based extended Kalman filter (EKF) approach for the Global Positioning System (GPS) navigation processing. The “soft-switching” IMM estimator obtains its estimate as a weighted sum of the individual estimates from a number of parallel filters matched to different motion modes of the platform. The proposed method is applied to the GPS navigation to increase the navigation estimation accuracy at the high dynamic regions while preserving (without sacrificing) the precision at the low dynamic regions. In the illustrated example, the vehicle motion is designed to cover a broad range of dynamic behaviors: constant velocity, constant acceleration, variable acceleration, and circular turn. Simulation results show that the IMM-based EKF can substantially improve overall navigation accuracy as compared to that of single model EKF. The mode probability of the proposed IMM filter is also depicted.


Keywords: GPS, interacting multiple model (IMM), extended Kalman filter (EKF)


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