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A Novel Scalar Adaptive Filter for Mitigating the Cycle Slip

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Authors

Lim, Jun Kyu; Park, Chan Gook; Lee, Min Su

Issue Date
2009-01-27
Citation
The Institute of Navigation 2009 International Technical Meeting
Abstract
This paper presents a novel scalar adaptive filter, which
is reformulated by additional acceleration term. The filter
continuously estimates the measurement noise covariance,
the velocity error covariance and the acceleration error
covariance. For estimating three covariances, we use the
innovation method for the measurement noise covariance
and the least square method for other covariances. In
order to verify the proposed filter performance, we
compared with Kalman filter and the conventional scalar
adaptive filer. We make indoor test bed using the
ultrasonic sensors. Experimental results show that the
proposed filter has better position accuracy than the
traditional scalar adaptive filter and Kalman filter.
Language
English
URI
https://hdl.handle.net/10371/72168
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