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1

Mobile Multi-Sensor Systems MMSS Research Group, Department of Geomatics Engineering, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada

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College of Automation, Harbin Engineering University, Harbin 150001, China

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GNSS Research Center, Wuhan University, 129 Luoyu Road, Wuhan 430079, China





*

Author to whom correspondence should be addressed.



Academic Editors: Aboelmagd Noureldin and Stefano Mariani

Abstract Numerous solutions-methods to solve the existing problems of pedestrian navigation-localization have been proposed in the last decade by both industrial and academic researchers. However, to date there are still major challenges for a single pedestrian navigation system PNS to operate continuously, robustly, and seamlessly in all indoor and outdoor environments. In this paper, a novel method for pedestrian navigation approach to fuse the information from two separate PNSs is proposed. When both systems are used at the same time by a specific user, a nonlinear inequality constraint between the two systems’ navigation estimates always exists. Through exploring this constraint information, a novel filtering technique named Kalman filter with state constraint is used to diminish the positioning errors of both systems. The proposed method was tested by fusing the navigation information from two different PNSs, one is the foot-mounted inertial navigation system INS mechanization-based system, the other PNS is a navigation device that is mounted on the user’s upper body, and adopting the pedestrian dead reckoning PDR mechanization for navigation update. Monte Carlo simulations and real field experiments show that the proposed method for the integration of multiple PNSs could improve each PNS’ navigation performance. View Full-Text

Keywords: pedestrian navigation system PNS; state constraint; Kalman filter; inertial navigation system INS; pedestrian dead reckoning PDR pedestrian navigation system PNS; state constraint; Kalman filter; inertial navigation system INS; pedestrian dead reckoning PDR





Autor: Haiyu Lan 1,2,* , Chunyang Yu 1, Yuan Zhuang 1, You Li 1,3 and Naser El-Sheimy 1

Fuente: http://mdpi.com/



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