Type

Conference Proceedings

Authors

Chris Bleakley
Nagesh Yadav

Subjects

Engineering

Topics
vectors estimation kalman filtering accelerometers gyroscopes biosensors biomedical measurements kalman filters

Two Stage Kalman Filtering for Position Estimation Using Dual Inertial Measurement Units (2011)

Abstract Herein a two stage Kalman filter based algorithm is proposed for processing of Inertial Measurement Unit (IMU) data to obtain accurate position estimation over a short period of time. The proposed algorithm uses a novel sensor placement strategy on rigid body. An Extended Kalman filter algorithm incorporates these placement constraints to achieve accurate position estimation. The results show 30% improvement in position estimation as compared to a conventional Dead Reckoning (DR) approach. To the best of the authors' knowledge, the proposed technique is the first which employs spatially separated dual IMUs on a single rigid body for position estimation.
Collections Ireland -> University College Dublin -> College of Science
Ireland -> University College Dublin -> School of Computer Science
Ireland -> University College Dublin -> Computer Science Research Collection

Full list of authors on original publication

Chris Bleakley, Nagesh Yadav

Experts in our system

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Chris Bleakley
University College Dublin
Total Publications: 105