基于卫星导航/惯性单元松耦合的低速智能电动汽车航向角估计

Heading Angle Estimation of Low-Speed Automated Electric Vehicle Based on Loosely Coupled Global Navigation Satellite System /Inertial Measurement Unit Integration

摘要:

低速智能电动汽车近年来发展迅速，组合定位技术是其关键技术，航向角估计是组合定位技术中重要组成部分。基于低速智能电动汽车，提出了GNSS(global navigation satellite system)/IMU(inertial measurement unit)组合的航向角估计方法。介绍了GNSS/IMU松耦合条件下的航向角估计方法，提出基于IMU的航向角积分方法，推导了松耦合条件下误差动态与测量模型。针对GNSS信号质量时变问题，使用残差自适应卡尔曼滤波算法对航向角误差进行估计。针对GNSS信号质量设计了航向角误差反馈修正策略。通过在不同GNSS信号条件下进行的多组实车试验，验证了所提出的航向角估计算法的有效性。

Abstract:

Low speed intelligent electric vehicle has been developing rapidly in recent years. The integrated localization method is the key technology in which the heading angle estimation is an important component. Based on low speed intelligent electric vehicle, a heading angle estimation method using the loosely coupled GNSS(global navigation satellite system)/IMU(inertial measurement unit) integration method is proposed in this paper. First, the heading angle estimation method is introduced. A heading angle integration method is proposed and the heading angle error dynamics and its measurement equation are derived. Aiming at the problem of time-varying quality of the GNSS signal, a residual adaptive estimation(RAE) Kalman filter is used. Then, an adaptive feedback strategy of heading error is adopted to reject the abnormal GNSS signal. Finally, under different GNSS signal conditions, the validity of the heading angle estimation method proposed in this paper is verified by multiple sets of real vehicle tests under different GNSS signal conditions.