A particle filter for Wi-Fi azimuth and position tracking with pedestrian dead reckoning

Conference contribution


Publication Details

Author(s): Thielecke J, Vaupel T, Seitz J
Title edited volumes: 2013 Workshop on Sensor Data Fusion: Trends, Solutions, Applications, SDF 2013
Publisher: IEEE Computer Society
Publication year: 2013
Conference Proceedings Title: 8th Workshop on Sensor Data Fusion: Trends, Solutions, Applications, SDF 2013
Pages range: 1-6
ISBN: 978-1-4799-0777-9


Abstract


A tracking algorithm for estimating the azimuth angle regarding north and a two-dimensional position of a mobile unit carried by a pedestrian is presented. Using Wi-Fi signal strength measurements the position of a mobile receiver can be estimated using so called fingerprinting methods. If the signal strengths measurements are collected with directional antennas additionally the azimuth can be estimated. For sensor data fusion of Wi-Fi signal strength measurements, acceleration measurements and angular rate measurements a particle filter is presented. The well known Wi-Fi fingerprinting approach is used to calculate the particle weights and pedestrian dead reckoning to sample the particles. Measurements have been collected inside and outside of an office building to evaluate the performance. Including step detection based on acceleration measurements reduces mainly the positioning error, including angular rate measurements reduces mainly the azimuth estimation error. Electronic compasses, which are susceptible to faults, are not needed to estimate the azimuth indoors. Especially in indoor environments this approach facilitates the use of electronic guides that offer additional information by means of augmented reality, e.g. on museum exhibits in visual range. © 2013 IEEE.



FAU Authors / FAU Editors

Seitz, Jochen
Lehrstuhl für Informationstechnik mit dem Schwerpunkt Kommunikationselektronik (Stiftungslehrstuhl)
Thielecke, Jörn Prof. Dr.
Professur für Informationstechnik (Schwerpunkt Ortsbestimmung und Navigation)


How to cite

APA:
Thielecke, J., Vaupel, T., & Seitz, J. (2013). A particle filter for Wi-Fi azimuth and position tracking with pedestrian dead reckoning. In 8th Workshop on Sensor Data Fusion: Trends, Solutions, Applications, SDF 2013 (pp. 1-6). Bonn, Germany, DE: IEEE Computer Society.

MLA:
Thielecke, Jörn, Thorsten Vaupel, and Jochen Seitz. "A particle filter for Wi-Fi azimuth and position tracking with pedestrian dead reckoning." Proceedings of the 8th Workshop on Sensor Data Fusion: Trends, Solutions, Applications, SDF 2013, Bonn, Germany IEEE Computer Society, 2013. 1-6.

BibTeX: 

Last updated on 2018-19-04 at 02:52