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A Doppler enhanced TDCP algorithm based on terrain adaptive and robust Kalman filter using a stand-alone receiver

Published online by Cambridge University Press:  05 July 2022

Kefan Shao ,
Zengke Li ,
Zhehua Yang ,
Zan Liu  and
Yaowen Sun
Kefan Shao
Affiliation:
School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China Jiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou, China
Zengke Li*
Affiliation:
School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China Jiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou, China
Zhehua Yang
Affiliation:
School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China Jiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou, China
Zan Liu
Affiliation:
School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China Jiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou, China
Yaowen Sun
Affiliation:
School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China Jiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou, China
*
*Corresponding author. E-mail: zengkeli@yeah.net
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Abstract

Time-differenced carrier phase (TDCP) is a commonly used method of precise velocimetry, but when the receiver is in a dynamic or complex observation environment, the estimation accuracy is reduced. Doppler velocimetry aims at estimating instantaneous velocity, and the accuracy is restricted by the accuracy of measurement. However, in such unfavourable cases, the Doppler measurement is more reliable than the carrier phase measurement. This paper derives the relationship between Doppler observation and TDCP observation, then proposes a Doppler enhanced TDCP algorithm, for the purpose of improving the velocity estimation accuracy in dynamic and complex observation environments. In addition, considering the error caused by the constant speed state update model in the robust Kalman filter (RKF), this paper designs a terrain adaptive and robust Kalman filter (TARKF). After three experimental tests, the improved TDCP algorithm can significantly increase the speed measurement accuracy to sub-metre per second, and the accuracy can be further improved after using TARKF.

Keywords

GNSS velocityterrain adaptive and robust Kalman filtertime-differenced carrier phaseDoppler
Type
Research Article
Information
The Journal of Navigation , Volume 75 , Issue 4 , July 2022 , pp. 864 - 877
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Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press on behalf of The Royal Institute of Navigation

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