Improved orientation estimation in complex environments using low-cost inertial sensors
Date
2011
Authors
Johnson, M. E.
Sathyan, Thuraiappah
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Conference paper
Citation
2011 Proceedings of the 14th International Conference on Information Fusion (FUSION 2011): pp.1-8
Statement of Responsibility
M. E. Johnson, T. Sathyan
Conference Name
International Conference on Information Fusion (14th : 2011 : Chicago, Illinois, U.S.A.)
FUSION '11
FUSION '11
Abstract
Localization in outdoor environments is widespread, providing improved functionality and benefits for many applications. Extending this ability to in-building environments is a critical prerequisite for many location aware services. Low cost inertial sensors have the potential to improve the performance of new and existing localization systems. A challenging problem in inertial navigation is the accurate tracking of orientation. In this paper we propose a new orientation tracking algorithm that uses a complementary Kalman filter (CKF) for obtaining a reference orientation. A feedback loop is developed, which estimates the gyro bias from the CKF reference. The final orientation is the direct integration of the gyro, after removing the estimated bias. Experimental results show that the proposed algorithm provides significantly improved orientation estimates in the presence of magnetic anomalies and sensor movement, as well as increased stability and reduced noise compared the original CKF algorithm. Position calculations, using a zero-velocity update process, demonstrate the advantages of the enhanced orientation estimate as clear improvements in consequent localization.
School/Discipline
School of Computer Science
Dissertation Note
Provenance
Description
Access Status
Rights
©2011 IEEE