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ISPRS Int. J. Geo-Inf. 2017, 6(8), 235; doi:10.3390/ijgi6080235

The IMU/UWB Fusion Positioning Algorithm Based on a Particle Filter

School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China
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Received: 9 June 2017 / Revised: 3 July 2017 / Accepted: 3 August 2017 / Published: 7 August 2017
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Abstract

This paper integrates UWB (ultra-wideband) and IMU (Inertial Measurement Unit) data to realize pedestrian positioning through a particle filter in a non-line-of-sight (NLOS) environment. After the acceleration and angular velocity are integrated by the ZUPT-based algorithm, the velocity and orientation of the feet are obtained, and then the velocity and orientation of the whole body are estimated by a virtual odometer method. This information will be adopted as the prior information for the particle filter, and the observation value of UWB will act as the basis for weight updating. According to experimental results, the prior information provided by an IMU can be used to restrain the observation error of UWB under an NLOS condition, and the positioning precision can be improved from the positioning error of 1.6 m obtained using the pure UWB-based algorithm to approximately 0.7 m. Moreover, with high computational efficiency, this algorithm can achieve real-time computing performance on ordinary embedded devices. View Full-Text
Keywords: UWB/INS; ZUPT; particle filter; indoor location UWB/INS; ZUPT; particle filter; indoor location
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Wang, Y.; Li, X. The IMU/UWB Fusion Positioning Algorithm Based on a Particle Filter. ISPRS Int. J. Geo-Inf. 2017, 6, 235.

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