An Improved Robust Kalman Filtering Method Based on Innovation and Its Application in UWB Indoor Navigation

LIU Tao; XU Aigong; SUI Xin; WANG Changqiang

doi:10.13203/j.whugis20170067

Volume 44 Issue 2

Feb. 2019

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Geomatics and Information Science of Wuhan University > 2019 > 44(2): 233-239. > DOI: 10.13203/j.whugis20170067

LIU Tao, XU Aigong, SUI Xin, WANG Changqiang. An Improved Robust Kalman Filtering Method Based on Innovation and Its Application in UWB Indoor Navigation[J]. Geomatics and Information Science of Wuhan University, 2019, 44(2): 233-239. DOI: 10.13203/j.whugis20170067

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An Improved Robust Kalman Filtering Method Based on Innovation and Its Application in UWB Indoor Navigation

LIU Tao^1,,
XU Aigong^1, ,,
SUI Xin^{1, 2},
WANG Changqiang¹

1.
School of Geomatics, Liaoning Technical University, Fuxin 123000, China
2.
Research Center of GNSS, Wuhan University, Wuhan 430079, China

Funds:

The National Key Research and Development Program of China 2016YFC0803102

Program for Colleges and Universities Innovative Research Team of Liaoning Province LT2015013

More Information

Author Bio:
LIU Tao, master, specializes in indoor navigation and positioning by UWB and UWB/INS coupled method. E-mail: 851273623@qq.com
Corresponding author:
XU Aigoing, PhD, professor. E-mail:xu_ag@126.com
Received Date: September 03, 2017
Published Date: February 04, 2019

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Abstract

Abstract

In UWB indoor navigation, the accuracy of navigation resolution is greatly affected by non line of sight(NLOS) ranging error, and low filtering precision is influenced by uncertain system noise. To solve these problems, an improved robust Kalman filtering based on innovation is proposed and applied in ultra wideband(UWB) indoor navigation. On the foundation of the linear UWB indoor navigation model, the new method uses single innovation values to construct the matrix with robust factors and eliminate the influence of NLOS ranging error. Meanwhile, the new method does real-time estimation and corrects the system noise covariance matrix. Experimental result verifies the effectiveness of the new method. It is shown that the new method can not only effectively eliminate the influence of NLOS ranging error on navigation resolution, but also can further improve the filter precision and reliability in indoor navigation.
- UWB indoor navigation,
- robust estimation,
- Kalman filtering,
- NLOS ranging error,
- innovation

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References

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