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Improved Adaptive Iterated Extended Kalman Filter for GNSS/INS/UWB-Integrated Fixed-Point Positioning

Qingdong Wu1, Chenxi Li2, Tao Shen2, Yuan Xu2,3,*

1 Shandong Luqiao Group Co., Ltd., Jinan, 250014, China
2 School of Electrical Engineering, University of Jinan, Jinan, 250022, China
3 Shandong Beiming Medical Technology Co., Ltd., Jinan, 250022, China

* Corresponding Author: Yuan Xu. Email: email

(This article belongs to this Special Issue: Advances on Modeling and State Estimation for Industrial Processes)

Computer Modeling in Engineering & Sciences 2023, 134(3), 1761-1772. https://doi.org/10.32604/cmes.2022.020545

Abstract

To provide stable and accurate position information of control points in a complex coastal environment, an adaptive iterated extended Kalman filter (AIEKF) for fixed-point positioning integrating global navigation satellite system, inertial navigation system, and ultra wide band (UWB) is proposed. In this method, the switched global navigation satellite system (GNSS) and UWB measurement are used as the measurement of the proposed filter. For the data fusion filter, the expectation-maximization (EM) based IEKF is used as the forward filter, then, the Rauch-Tung-Striebel smoother for IEKF filter’s result smoothing. Tests illustrate that the proposed AIEKF is able to provide an accurate estimation.

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Cite This Article

Wu, Q., Li, C., Shen, T., Xu, Y. (2023). Improved Adaptive Iterated Extended Kalman Filter for GNSS/INS/UWB-Integrated Fixed-Point Positioning. CMES-Computer Modeling in Engineering & Sciences, 134(3), 1761–1772.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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