Online Estimation of the Mounting Angle and the Lever Arm for a Low-Cost Embedded Integrated Navigation Module

被引:1
作者
Wang, Qinghai [1 ]
Yan, Peihui [1 ,2 ]
Jiang, Jinguang [1 ,3 ,4 ]
Xie, Dongpeng [1 ]
Li, Yuying [1 ]
Zheng, Qiyuan [1 ]
Tan, Hongbin [1 ]
Wu, Jiaji [1 ]
机构
[1] Wuhan Univ, GNSS Res Ctr, Wuhan 430079, Peoples R China
[2] Wuhan Univ, Student Engn Training & Innovat Practice Ctr, 129 Luoyu Rd, Wuhan 430072, Peoples R China
[3] Hubei Luojia Lab BDS Chip Res Ctr, 129 Luoyu Rd, Wuhan 430079, Peoples R China
[4] Wuhan Univ, Sch Microelect, Wuhan 430079, Peoples R China
关键词
mounting angles; lever arm; integrated navigation; GNSS; inertial navigation; Kalman filter; INITIAL ALIGNMENT METHOD; CALIBRATION METHOD; VEHICLE; SENSORS;
D O I
10.3390/rs16163064
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Multi-source fusion constitutes a research focus in the navigation domain. This article focuses on the online estimation of the mounting angles between the body frame and vehicle frame within low-cost embedded vehicle navigation modules and the lever arm between the global satellite navigation system (GNSS) antenna/odometer and the inertial measurement unit (IMU). An online mounting angle error estimation algorithm, using odometers and IMU speeds, has been developed to estimate the angle errors while vehicles are in motion. At the same time, an online estimation algorithm model for the GNSS antenna lever arm and odometer lever arm was constructed. These two types of lever arms are used as the estimated states, and then Kalman filters are used to estimate them. The algorithm can simultaneously estimate the IMU mounting angle error, GNSS antenna arm, and odometer arm online. The experimental outcomes demonstrate that the lever arm estimation algorithm presented herein is effective for tactical and MEMS-level inertial navigation, with an estimation error of less than 2 cm. Meanwhile, the proposed online estimation of the mounting angle algorithm has an accuracy comparable to that of the post-processing algorithm. After making up the mounting angle and lever arm, we found that the position and speed precision of the multi-source fusion navigation systems were significantly improved. The results indicate that the proposed online estimation of mounting angle error and lever arm algorithm are effective and may promote the practical and widespread application of integrated navigation systems in vehicles. It solves the shortcomings of traditional methods, including the cumbersome and inaccurate manual measurement of the lever arm. It provides a technical solution for developing a more accurate and convenient low-cost vehicle navigation module.
引用
收藏
页数:20
相关论文
共 35 条
[21]   Motion model-assisted GNSS/MEMS-IMU integrated navigation system for land vehicle [J].
Sun, Yaowen ;
Li, Zengke ;
Yang, Zhehua ;
Shao, Kefan ;
Chen, Wangqi .
GPS SOLUTIONS, 2022, 26 (04)
[22]   A Novel INS and Doppler Sensors Calibration Method for Long Range Underwater Vehicle Navigation [J].
Tang, Kanghua ;
Wang, Jinling ;
Li, Wanli ;
Wu, Wenqi .
SENSORS, 2013, 13 (11) :14583-14600
[23]   Mounting-Angle Estimation for Personal Navigation Devices [J].
Vinande, Eric ;
Axelrad, Penina ;
Akos, Dennis .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2010, 59 (03) :1129-1138
[24]  
Wang Q., 2012, P 31 CHIN CONTR C HE
[25]  
[王志伟 Wang Zhiwei], 2018, [压电与声光, Piezoelectrics and Acoustooptics], V40, P428
[26]  
Weng Jun, 2013, Chinese Journal of Sensors and Actuators, V26, P1232, DOI 10.3969/j.issn.1004-1699.2013.09.011
[27]  
Wu Y., 2009, PROC AIAA GUID NAVIG, P5970
[28]   Dynamic Calibration Method for SINS Lever-Arm Effect for HCVs [J].
Xiong, Zhi ;
Peng, Hui ;
Wang, Jie ;
Wang, Rong ;
Liu, Jian-Ye .
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2015, 51 (04) :2760-2771
[29]   A Novel Autonomous Initial Alignment Method for Strapdown Inertial Navigation System [J].
Xu, Jiangning ;
He, Hongyang ;
Qin, Fangjun ;
Chang, Lubin .
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2017, 66 (09) :2274-2282
[30]  
[严恭敏 YAN Gongmin], 2008, [中国惯性技术学报, Journal of Chinese Inertial Technology Eng], V16, P148