Rapid Initial Heading Alignment for MEMS Land Vehicular GNSS/INS Navigation System

被引:10
|
作者
Chen, Qijin [1 ,2 ]
Lin, Huan [1 ]
Kuang, Jian [1 ]
Luo, Yarong [1 ]
Niu, Xiaoji [1 ,2 ]
机构
[1] Wuhan Univ, GNSS Res Ctr, Wuhan 430072, Peoples R China
[2] Hubei Luojia Lab, Wuhan 430079, Peoples R China
基金
中国国家自然科学基金;
关键词
Global navigation satellite system; Trajectory; Micromechanical devices; Vehicle dynamics; Transforms; Position measurement; Kalman filters; Dead reckoning (DR); global navigation satellite system (GNSS); inertial navigation system (INS) integration; initial alignment; in-motion alignment; land vehicular navigation; microelectromechanical system (MEMS) INS; OPTIMIZATION-BASED ALIGNMENT; MOTION COARSE ALIGNMENT; VEHICLE; GPS; ATTITUDE;
D O I
10.1109/JSEN.2023.3247587
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
For the low-cost microelectromechanical system (MEMS) inertial navigation system (INS) and the global navigation satellite system (GNSS)-integrated system in land vehicular applications, quick and accurate coarse alignment is still a challenge, especially for a host vehicle that moves at low speed under low dynamics. In this article, we propose an in-motion coarse initial heading alignment algorithm for the low-cost MEMS INS aided by the GNSS, which is specifically designed for land vehicular conditions. The principle of the proposed method is straightforward when considered in the context of trajectory matching: the MEMS can compute a relative vehicle trajectory through a dead reckoning (DR) calculator using the gyro-derived attitude solution and the travel distance, and the GNSS can provide an absolute vehicle trajectory through its positioning solution. The initial heading is then computed by comparing these DR-indicated and GNSS-indicated trajectories. The proposed algorithm is verified using a civilian vehicle, a wheeled robot, and an agricultural tractor under different motion and dynamic conditions. The results show that the initial heading could be quickly determined with an accuracy of 0.25 degrees, 0.6 degrees, and 1.6 degrees at a 98.6% confidence level within 5 s for the car, robot, and tractor tests, respectively.
引用
收藏
页码:7656 / 7666
页数:11
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