Title :
Optimal data fusion for pedestrian navigation based on UWB and MEMS
Author :
Renaudin, V. ; Merminod, B. ; Kasser, M.
Author_Institution :
Ecole Polytech. Fed. de Lausanne, Lausanne
Abstract :
Indoor pedestrian navigation is probably a very challenging research area. In this context, an optimal data fusion filter that hybridises a large set of observations: angles of arrival (AOA), time differences of arrival (TDOA), accelerations, angular velocities and magnetic field measurements is presented. The coupling of UWB and MEMS data relies on an extended Kalman filter complemented with specific procedures. Geometry based algorithms and a RANSAC paradigm that mitigates the non line of sight (NLOS) UWB propagation are detailed. The benefit of the solution is evaluated and compared with the pure inertial positioning system.
Keywords :
Kalman filters; direction-of-arrival estimation; indoor radio; micromechanical devices; radio direction-finding; radiowave propagation; sensor fusion; MEMS; RANSAC paradigm; angles of arrival; angular velocities; extended Kalman filter; geometry based algorithms; indoor pedestrian navigation; inertial positioning system; magnetic field measurements; nonline-of-sight UWB propagation; optimal data fusion filter; time differences of arrival; Acceleration; Angular velocity; Antennas and propagation; Bluetooth; Geometry; Humans; Magnetic field measurement; Micromechanical devices; Navigation; Radiofrequency identification;
Conference_Titel :
Position, Location and Navigation Symposium, 2008 IEEE/ION
Conference_Location :
Monterey, CA
Print_ISBN :
978-1-4244-1536-6
Electronic_ISBN :
978-1-4244-1537-3
DOI :
10.1109/PLANS.2008.4570054
