NDLI: An improved indoor localization method using smartphone inertial sensors

Content Provider	IEEE Xplore Digital Library
Author	Jiuchao Qian Jiabin Ma Rendong Ying Peilin Liu Ling Pei
Copyright Year	2013
Description	Author affiliation: Sch. of Electron. Inf. & Electr. Eng., Shanghai Jiao Tong Univ. (SJTU), Shanghai, China (Jiuchao Qian; Jiabin Ma; Rendong Ying; Peilin Liu; Ling Pei)
Abstract	In this paper, an improved indoor localization method based on smartphone inertial sensors is presented. Pedestrian dead reckoning (PDR), which determines the relative location change of a pedestrian without additional infrastructure supports, is combined with a floor plan for a pedestrian positioning in our work. To address the challenges of low sampling frequency and limited processing power in smartphones, reliable and efficient PDR algorithms have been proposed. A robust step detection technique leaves out the preprocessing of raw signal and reduces complex computation. Given the fact that the precision of the stride length estimation is influenced by different pedestrians and motion modes, an adaptive stride length estimation algorithm based on the motion mode classification is developed. Heading estimation is carried out by applying the principal component analysis (PCA) to acceleration measurements projected to the global horizontal plane, which is independent of the orientation of a smartphone. In addition, to eliminate the sensor drift due to the inaccurate distance and direction estimations, a particle filter is introduced to correct the drift and guarantee the localization accuracy. Extensive field tests have been conducted in a laboratory building to verify the performance of proposed algorithm. A pedestrian held a smartphone with arbitrary orientation in the tests. Test results show that the proposed algorithm can achieve significant performance improvements in terms of efficiency, accuracy and reliability.
Sponsorship	IEEE
Starting Page	1
Ending Page	7
File Size	1423474
Page Count	7
File Format	PDF
ISBN	9781479940431
DOI	10.1109/IPIN.2013.6817854
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-10-28
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Legged locomotion Navigation Estimation Indoor localization Particle filters Sensors Acceleration Particle filter Principal component analysis PDR PCA
Content Type	Text
Resource Type	Article

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