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

被引：0
|
作者：
Ge, Baoshuang [1 ]
Zhang, Hai [1 ]
Fu, Wenxing [2 ]
Chen, Jieling [3 ]
机构：
[1] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing, Peoples R China
[2] Sci & Technol Complex Syst Control & Intelligent, Beijing, Peoples R China
[3] China Ship Dev & Design Ctr, Wuhan, Peoples R China
来源：
2020 THE 5TH INTERNATIONAL CONFERENCE ON CONTROL AND ROBOTICS ENGINEERING (ICCRE 2020) | 2020年
关键词：
integrated navigation; micro-electromechanical systems (MEMS) barometer; velocity constraints; vehicle positioning;
D O I：
10.1109/iccre49379.2020.9096484
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
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.
引用
收藏
页码：159 / 163
页数：5
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