Low-Cost INS/GNSS Integration Algorithm Aided by Multi-Constraints Applied to Vehicle Navigation

Baoshuang Ge; Hai Zhang; Wenxing Fu; Jieling Chen

doi:10.1109/ICCRE49379.2020.9096484

Low-Cost INS/GNSS Integration Algorithm Aided by Multi-Constraints Applied to Vehicle Navigation

Baoshuang Ge, Hai Zhang, Wenxing Fu, Jieling Chen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

The low-cost inertial navigation system/global navigation satellite system (INS/GNSS) integration has been widely used to vehicle navigation. However, the positioning performance often declines due to the weak satellite signals. This paper presents a new approach to improve the accuracy of the vehicle navigation. In contrast to the current methods, a new velocity constraint model is developed to aid the estimation of the navigation errors. The altitude accuracy of GNSS is challenged in comparison with its position in the horizonal plane. Thus, an auxiliary low-cost barometer is used to obtain the height as well. The experimental results demonstrate the benefit of the proposed multi-constraints aiding algorithm.

Original language	English
Title of host publication	2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	159-163
Number of pages	5
ISBN (Electronic)	9781728167916
DOIs	https://doi.org/10.1109/ICCRE49379.2020.9096484
State	Published - Apr 2020
Externally published	Yes
Event	5th International Conference on Control and Robotics Engineering, ICCRE 2020 - Osaka, Japan Duration: 24 Apr 2020 → 26 Apr 2020

Publication series

Name	2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020

Conference

Conference	5th International Conference on Control and Robotics Engineering, ICCRE 2020
Country/Territory	Japan
City	Osaka
Period	24/04/20 → 26/04/20

Keywords

integrated navigation
micro-electromechanical systems (MEMS) barometer
vehicle positioning
velocity constraints

Access to Document

10.1109/ICCRE49379.2020.9096484

Cite this

Ge, B., Zhang, H., Fu, W., & Chen, J. (2020). Low-Cost INS/GNSS Integration Algorithm Aided by Multi-Constraints Applied to Vehicle Navigation. In 2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020 (pp. 159-163). Article 9096484 (2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCRE49379.2020.9096484

Ge, Baoshuang ; Zhang, Hai ; Fu, Wenxing et al. / Low-Cost INS/GNSS Integration Algorithm Aided by Multi-Constraints Applied to Vehicle Navigation. 2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 159-163 (2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020).

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title = "Low-Cost INS/GNSS Integration Algorithm Aided by Multi-Constraints Applied to Vehicle Navigation",

abstract = "The low-cost inertial navigation system/global navigation satellite system (INS/GNSS) integration has been widely used to vehicle navigation. However, the positioning performance often declines due to the weak satellite signals. This paper presents a new approach to improve the accuracy of the vehicle navigation. In contrast to the current methods, a new velocity constraint model is developed to aid the estimation of the navigation errors. The altitude accuracy of GNSS is challenged in comparison with its position in the horizonal plane. Thus, an auxiliary low-cost barometer is used to obtain the height as well. The experimental results demonstrate the benefit of the proposed multi-constraints aiding algorithm.",

keywords = "integrated navigation, micro-electromechanical systems (MEMS) barometer, vehicle positioning, velocity constraints",

author = "Baoshuang Ge and Hai Zhang and Wenxing Fu and Jieling Chen",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 5th International Conference on Control and Robotics Engineering, ICCRE 2020 ; Conference date: 24-04-2020 Through 26-04-2020",

year = "2020",

month = apr,

doi = "10.1109/ICCRE49379.2020.9096484",

language = "英语",

series = "2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "159--163",

booktitle = "2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020",

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Ge, B, Zhang, H, Fu, W & Chen, J 2020, Low-Cost INS/GNSS Integration Algorithm Aided by Multi-Constraints Applied to Vehicle Navigation. in 2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020., 9096484, 2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020, Institute of Electrical and Electronics Engineers Inc., pp. 159-163, 5th International Conference on Control and Robotics Engineering, ICCRE 2020, Osaka, Japan, 24/04/20. https://doi.org/10.1109/ICCRE49379.2020.9096484

Low-Cost INS/GNSS Integration Algorithm Aided by Multi-Constraints Applied to Vehicle Navigation. / Ge, Baoshuang; Zhang, Hai; Fu, Wenxing et al.
2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020. Institute of Electrical and Electronics Engineers Inc., 2020. p. 159-163 9096484 (2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - The low-cost inertial navigation system/global navigation satellite system (INS/GNSS) integration has been widely used to vehicle navigation. However, the positioning performance often declines due to the weak satellite signals. This paper presents a new approach to improve the accuracy of the vehicle navigation. In contrast to the current methods, a new velocity constraint model is developed to aid the estimation of the navigation errors. The altitude accuracy of GNSS is challenged in comparison with its position in the horizonal plane. Thus, an auxiliary low-cost barometer is used to obtain the height as well. The experimental results demonstrate the benefit of the proposed multi-constraints aiding algorithm.

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KW - micro-electromechanical systems (MEMS) barometer

KW - vehicle positioning

KW - velocity constraints

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Ge B, Zhang H, Fu W, Chen J. Low-Cost INS/GNSS Integration Algorithm Aided by Multi-Constraints Applied to Vehicle Navigation. In 2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 159-163. 9096484. (2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020). doi: 10.1109/ICCRE49379.2020.9096484

Low-Cost INS/GNSS Integration Algorithm Aided by Multi-Constraints Applied to Vehicle Navigation

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