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

^*此作品的通讯作者

自动化科学与电气工程学院

Beihang University
Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory
China Ship Development and Design Centre

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

5 引用（Scopus）

摘要

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.

源语言	英语
主期刊名	2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020
出版商	Institute of Electrical and Electronics Engineers Inc.
页	159-163
页数	5
ISBN（电子版）	9781728167916
DOI	https://doi.org/10.1109/ICCRE49379.2020.9096484
出版状态	已出版 - 4月 2020
活动	5th International Conference on Control and Robotics Engineering, ICCRE 2020 - Osaka, 日本期限: 24 4月 2020 → 26 4月 2020

出版系列

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

会议

会议	5th International Conference on Control and Robotics Engineering, ICCRE 2020
国家/地区	日本
市	Osaka
时期	24/04/20 → 26/04/20

访问文件

10.1109/ICCRE49379.2020.9096484

其它文件与链接

链接到 Scopus 的出版物

引用此

Ge, B., Zhang, H., Fu, W., & Chen, J. (2020). Low-Cost INS/GNSS Integration Algorithm Aided by Multi-Constraints Applied to Vehicle Navigation. 在 2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020 (页码 159-163). 文章 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 等. / 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. 页码 159-163 (2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020).

@inproceedings{61a322d1f10d45339d6d8f312a1a86ae,

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",

address = "美国",

}

Ge, B, Zhang, H, Fu, W & Chen, J 2020, Low-Cost INS/GNSS Integration Algorithm Aided by Multi-Constraints Applied to Vehicle Navigation. 在 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., 页码 159-163, 5th International Conference on Control and Robotics Engineering, ICCRE 2020, Osaka, 日本, 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 等.
2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020. Institute of Electrical and Electronics Engineers Inc., 2020. 页码 159-163 9096484 (2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Low-Cost INS/GNSS Integration Algorithm Aided by Multi-Constraints Applied to Vehicle Navigation

AU - Ge, Baoshuang

AU - Zhang, Hai

AU - Fu, Wenxing

AU - Chen, Jieling

PY - 2020/4

Y1 - 2020/4

N2 - 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.

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.

KW - integrated navigation

KW - micro-electromechanical systems (MEMS) barometer

KW - vehicle positioning

KW - velocity constraints

UR - https://www.scopus.com/pages/publications/85085976987

U2 - 10.1109/ICCRE49379.2020.9096484

DO - 10.1109/ICCRE49379.2020.9096484

M3 - 会议稿件

AN - SCOPUS:85085976987

T3 - 2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020

SP - 159

EP - 163

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

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 5th International Conference on Control and Robotics Engineering, ICCRE 2020

Y2 - 24 April 2020 through 26 April 2020

ER -

Ge B, Zhang H, Fu W, Chen J. Low-Cost INS/GNSS Integration Algorithm Aided by Multi-Constraints Applied to Vehicle Navigation. 在 2020 5th International Conference on Control and Robotics Engineering, ICCRE 2020. Institute of Electrical and Electronics Engineers Inc. 2020. 页码 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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