NDLI: An efficient bias estimation method in multisensor fusion for navigation by adaptive prototype selection in a bank of Kalman filters

Content Provider	IEEE Xplore Digital Library
Author	Insik Sen Sunmee Kang Chein-I Chang Hanseok Ko
Copyright Year	1999
Description	Author affiliation: Korea Telecom, Seoul, South Korea (Insik Sen)
Abstract	A navigation system usually employs multiple sensors to combine the strength of individual sensors such as GPS, gyroscope, and accelerometer. However, the multiple sensor fusion for navigation objectives encounters noise and time-variant bias present in individual sensor measurement. This paper proposes an efficient method to estimate the unknown bias for cancellation in a fused navigation system involving multiple sensors using an adaptive bias prototype selection employed over a bank of parallel Kalman filters. The conventional method which focuses on a special case of bias characteristics revolving around the semi-Markov process model is recognized for its excessive computation if the bias prototype set is chosen too large. This means that a huge discrete set of bias is needed to obtain the bias estimation accurately. Focusing on solving the problem of large bias prototypes, we propose a two-step selection process: (1) the decision part that locks on a new bias set from estimated bias covariance and (2) the balance part that regulates the newly selected bias set to enable a smooth transition under inadvertent bias overshoots. Simulation results show a substantial improvement in bias estimation accuracy while maintaining a minimal computation compared to the nonadaptive randomly switching bias estimators.
Starting Page	279
Ending Page	284
File Size	386719
Page Count	6
File Format	PDF
ISBN	0780358015
DOI	10.1109/MFI.1999.816003
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-08-18
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Navigation Sensor systems Sensor fusion Prototypes Sensor phenomena and characterization Global Positioning System Gyroscopes Accelerometers Noise cancellation Noise measurement
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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