Adaptive Kalman Filtering for INS/GPS |
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| Authors: | A H Mohamed K P Schwarz |
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| Institution: | (1) Department of Geomatics Engineering, The University of Calgary, 2500 University Drive NW, Calgary, Alberta, Canada T2N 1N4, CA |
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| Abstract: | After reviewing the two main approaches of adaptive Kalman filtering, namely, innovation-based adaptive estimation (IAE)
and multiple-model-based adaptive estimation (MMAE), the detailed development of an innovation-based adaptive Kalman filter
for an integrated inertial navigation system/global positioning system (INS/GPS) is given. The developed adaptive Kalman filter
is based on the maximum likelihood criterion for the proper choice of the filter weight and hence the filter gain factors.
Results from two kinematic field tests in which the INS/GPS was compared to highly precise reference data are presented. Results
show that the adaptive Kalman filter outperforms the conventional Kalman filter by tuning either the system noise variance–covariance
(V–C) matrix `Q' or the update measurement noise V–C matrix `R' or both of them.
Received: 14 September 1998 / Accepted: 21 December 1998 |
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| Keywords: | , Adaptive,Kalman filtering,GPS/INS |
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