GPS positioning algorithm based on UKF

Kang Wang; Li Liu; Xiao Jing Du; Huai Jian Li

doi:10.3873/j.issn.1000-1328.2011.04.014

GPS positioning algorithm based on UKF

Kang Wang^*, Li Liu, Xiao Jing Du, Huai Jian Li

^*Corresponding author for this work

School of Aerospace Engineering

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

10 Citations (Scopus)

Abstract

The extended Kalman filter deals with nonlinear problems using Taylor series expansion, leading to degraded performance. The UKF is adopted for GPS positioning in this paper. After formulating the UKF algorithm, a relationship between the linearized approximation error of GPS pseudorange equation and the positioning error is analyzed. The validity of UKF in GPS positioning is discussed. Pseudorange and Doppler shift measurements are used and the current statistics model is utilized in data processing. Simulation and field experiment are carried out by employing Spirent GPS simulator and NovAtel differential positioning system as well as NovAtel receiver, respectively. The results show that UKF has better performance than EKF when there are large errors in initial state values of the system.

Original language	English
Pages (from-to)	795-801
Number of pages	7
Journal	Yuhang Xuebao/Journal of Astronautics
Volume	32
Issue number	4
DOIs	https://doi.org/10.3873/j.issn.1000-1328.2011.04.014
Publication status	Published - Apr 2011

Keywords

GPS
Positioning
UKF

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10.3873/j.issn.1000-1328.2011.04.014

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Wang, K., Liu, L., Du, X. J., & Li, H. J. (2011). GPS positioning algorithm based on UKF. Yuhang Xuebao/Journal of Astronautics, 32(4), 795-801. https://doi.org/10.3873/j.issn.1000-1328.2011.04.014

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abstract = "The extended Kalman filter deals with nonlinear problems using Taylor series expansion, leading to degraded performance. The UKF is adopted for GPS positioning in this paper. After formulating the UKF algorithm, a relationship between the linearized approximation error of GPS pseudorange equation and the positioning error is analyzed. The validity of UKF in GPS positioning is discussed. Pseudorange and Doppler shift measurements are used and the current statistics model is utilized in data processing. Simulation and field experiment are carried out by employing Spirent GPS simulator and NovAtel differential positioning system as well as NovAtel receiver, respectively. The results show that UKF has better performance than EKF when there are large errors in initial state values of the system.",

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author = "Kang Wang and Li Liu and Du, {Xiao Jing} and Li, {Huai Jian}",

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AU - Li, Huai Jian

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AB - The extended Kalman filter deals with nonlinear problems using Taylor series expansion, leading to degraded performance. The UKF is adopted for GPS positioning in this paper. After formulating the UKF algorithm, a relationship between the linearized approximation error of GPS pseudorange equation and the positioning error is analyzed. The validity of UKF in GPS positioning is discussed. Pseudorange and Doppler shift measurements are used and the current statistics model is utilized in data processing. Simulation and field experiment are carried out by employing Spirent GPS simulator and NovAtel differential positioning system as well as NovAtel receiver, respectively. The results show that UKF has better performance than EKF when there are large errors in initial state values of the system.

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GPS positioning algorithm based on UKF

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Keywords

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