@inproceedings{bc3669ffc84d475eaf5063f4cd8577f4,
title = "A particle filter approach for pedestrian dead reckoning using wearable sensors",
abstract = "In this paper, a pedestrian dead reckoning (PDR)method is proposed based on the particle filter frameworkwith map information measurements from both an inertialmeasurement unit (IMU) on the footwear and a global positioningsystem (GPS). The main challenging of computingPDR with IMU signals is that the biases of IMU sensors willresult in unbounded integration drift. Therefore, a new methodthat uses non-zero velocity data for zero-velocity update ofthe accelerometer biases is proposed. Also, a measurementequation for the rate-gyro biases using accelerometer measurementsare derived. We also show that some heuristic driftcanceling rules can be easily incorporated into the particlefilter framework. Experimental results show that the proposedmethod can effectively reduce the accumulation error from 42meters to 10 meters.",
keywords = "Foot-mounted IMU, Integration drift, Particle filter, Pedestrian dead reckoning, Pedestrian tracking",
author = "Hsu, {Yi Lin} and Chen, {Yan Ju} and Shih, {Sheng Wen}",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 10th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2016 ; Conference date: 06-07-2016 Through 08-07-2016",
year = "2016",
month = dec,
day = "21",
doi = "10.1109/IMIS.2016.97",
language = "English",
series = "Proceedings - 2016 10th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "26--32",
editor = "Fatos Xhafa and Leonard Barolli and Noriki Uchida",
booktitle = "Proceedings - 2016 10th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2016",
address = "United States",
}