A Novel Scalar Adaptive Filter for Mitigating the Cycle Slip

Jun Kyu Lim, Chan Gook Park Min Su Lee

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.
Published in:	Proceedings of the 2009 International Technical Meeting of The Institute of Navigation January 26 - 28, 2009 Disney's Paradise Pier Hotel Anaheim, CA
Pages:	391 - 395
Cite this article:	Lim, Jun Kyu, Lee, Chan Gook Park Min Su, "A Novel Scalar Adaptive Filter for Mitigating the Cycle Slip," Proceedings of the 2009 International Technical Meeting of The Institute of Navigation, Anaheim, CA, January 2009, pp. 391-395.
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