SINS/Odometer integrated navigation method based on adaptive strong tracking filter

被引：0
|
作者：
Li S. [1 ]
Huang F. [2 ]
Qiu S. [3 ]
Fan C. [1 ]
机构：
[1] School of Electronic Engineering, Tianjin University of Technology and Education, Tianjin
[2] School of Mechanical Engineering, Hebei University of Technology, Tianjin
[3] Beijing Leihang Shiji Technology Co., Ltd, Beijing
来源：
Huang, Fengrong (2015016@hebut.edu.cn) | 2018年 / Editorial Department of Journal of Chinese Inertial Technology卷 / 26期
关键词：
Cubature Kalman filter; Integrated navigation; Odometer; Strong tracking filter;
D O I：
10.13695/j.cnki.12-1222/o3.2018.02.003
中图分类号：
学科分类号：
摘要：
Due to that fact that the speedometer scale changes greatly in the process of driving a large wheeled vehicle, the speedometer's error requirements assigned by the vehicle positioning and orienting system cannot be satisfied. To solve this problem, a nonlinear filtering method is studied. By taking a cubature Kalman filter as the algorithm framework and applying the basic theory of strong tracking filter fading factor, an adaptive strong tracking filter algorithm of SINS/Odometer integrated navigation is constructed to achieve the real-time adaptive estimation and compensation of the odometer scale errors. Simulation analysis and running test verify the feasibility of this method, and show that the new method can eliminate the influence of the odometer error further than traditional strong tracking filter method. The test results demonstrate that the positioning accuracy is more than doubled, achieving the ideal precision of the inertial components. © 2018, Editorial Department of Journal of Chinese Inertial Technology. All right reserved.
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页码：156 / 161
页数：5
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