Integration of foot-mounted inertial sensors into a Bayesian location estimation framework

Author

Krach, Bernhard ; Robertson, Patrick

Author_Institution

German Aerosp. Center DLR, Inst. of Commun. & Navig., Wessling

fYear

2008

fDate

27-27 March 2008

Firstpage

55

Lastpage

61

Abstract

An algorithm for integrating foot-mounted inertial sensors into a Bayesian location estimation framework is presented. The proposed integration scheme is based on a cascaded estimation architecture. A lower Kalman filter is used to estimate the step-wise change of position and direction of the foot. These estimates are used in turn as measurements in an upper particle filter, which is able to incorporate nonlinear map-matching techniques. Experimental data is used to verify the proposed algorithm.

Keywords

Bayes methods; Kalman filters; navigation; sensors; Bayesian location estimation framework; Kalman filter; foot-mounted inertial sensor; nonlinear map matching; Accelerometers; Aerodynamics; Bayesian methods; Change detection algorithms; Foot; Particle filters; Particle measurements; Satellite navigation systems; Sensor systems; State estimation; Indoor Navigation; Inertial Integration; Map-Matching; Pedestrian Navigation;

fLanguage

English

Publisher

ieee

Conference_Titel

Positioning, Navigation and Communication, 2008. WPNC 2008. 5th Workshop on

Conference_Location

Hannover

Print_ISBN

978-1-4244-1798-8

Electronic_ISBN

978-1-4244-1799-5

Type

conf

DOI

10.1109/WPNC.2008.4510357

Filename

4510357