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An Intuitive Approach to Inertial Sensor Bias Estimation

An Intuitive Approach to Inertial Sensor Bias Estimation A simple approach to gyro and accelerometer bias estimation is proposed. It does not involve Kalman filtering or similar formal techniques. Instead, it is based on physical intuition and exploits a duality between gimbaled and strapdown inertial systems. The estimation problem is decoupled into two separate stages. At the first stage, inertial system attitude errors are corrected by means of a feedback from an external aid. In the presence of uncompensated biases, the steady-state feedback rebalances those biases and can be used to estimate them. At the second stage, the desired bias estimates are expressed in a closed form in terms of the feedback signal. The estimator has only three tunable parameters and is easy to implement and use. The tests proved the feasibility of the proposed approach for the estimation of low-cost MEMS inertial sensor biases on a moving land vehicle. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Navigation and Observation Hindawi Publishing Corporation

An Intuitive Approach to Inertial Sensor Bias Estimation

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Publisher
Hindawi Publishing Corporation
Copyright
Copyright © 2013 Vasiliy M. Tereshkov.
ISSN
1687-5990
eISSN
1687-6008
Publisher site
See Article on Publisher Site

Abstract

A simple approach to gyro and accelerometer bias estimation is proposed. It does not involve Kalman filtering or similar formal techniques. Instead, it is based on physical intuition and exploits a duality between gimbaled and strapdown inertial systems. The estimation problem is decoupled into two separate stages. At the first stage, inertial system attitude errors are corrected by means of a feedback from an external aid. In the presence of uncompensated biases, the steady-state feedback rebalances those biases and can be used to estimate them. At the second stage, the desired bias estimates are expressed in a closed form in terms of the feedback signal. The estimator has only three tunable parameters and is easy to implement and use. The tests proved the feasibility of the proposed approach for the estimation of low-cost MEMS inertial sensor biases on a moving land vehicle.

Journal

International Journal of Navigation and ObservationHindawi Publishing Corporation

Published: Jul 2, 2013

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