Moussa Mohamed, Moussa Adel, El-Sheimy Naser
Geomatics Engineering Department, University of Calgary, Calgary, AB T2N 1N4, Canada.
Department of Electrical Engineering, Port Said University, Port Said 42523, Egypt.
Sensors (Basel). 2019 Apr 4;19(7):1618. doi: 10.3390/s19071618.
Recently, land vehicle navigation, and especially by the use of low-cost sensors, has been the object of a huge level of research interest. Consumer Portable Devices (CPDs) such as tablets and smartphones are being widely used by many consumers all over the world. CPDs contain sensors (accelerometers, gyroscopes, magnetometer, etc.) that can be used for many land vehicle applications such as navigation. This paper presents a novel approach for estimating steering wheel angles using CPD accelerometers by attaching CPDs to the steering wheel. The land vehicle change of heading is then computed from the estimated steering wheel angle. The calculated change of heading is used to update the navigation filter to aid the onboard Inertial Measurement Unit (IMU) through the use of an Extended Kalman Filter (EKF) in GNSS-denied environments. Four main factors that may affect the steering wheel angle accuracy are considered and modeled during steering angle estimations: static onboard IMU leveling, inclination angle of the steering wheel, vehicle acceleration, and vehicle inclination. In addition, these factors are assessed for their effects on the final result. Therefore, three methods are proposed for steering angle estimation: non-compensated, partially-compensated, and fully-compensated methods. A road experimental test was carried out using a Pixhawk (PX4) navigation system, iPad Air, and the OBD-II interface. The average Root Mean Square Error (RMSE) of the change of heading estimated by the proposed method was 0.033 rad/s. A navigation solution was estimated while changes of heading and forward velocity updates were used to aid the IMU during different GNSS signal outages. The estimated navigation solution is enhanced when applying the proposed updates to the navigation filter by 91% and 97% for 60 s and 120 s of GNSS signal outage, respectively, compared to the IMU standalone solution.
最近，陆地车辆导航，尤其是通过使用低成本传感器进行的导航，已成为大量研究兴趣的对象。诸如平板电脑和智能手机之类的消费便携式设备（CPD）正在被全球许多消费者广泛使用。CPD包含可用于许多陆地车辆应用（如导航）的传感器（加速度计、陀螺仪、磁力计等）。本文提出了一种通过将CPD连接到方向盘，利用CPD加速度计估计方向盘角度的新方法。然后根据估计的方向盘角度计算陆地车辆航向的变化。计算出的航向变化用于更新导航滤波器，以便在全球导航卫星系统（GNSS）信号缺失的环境中，通过使用扩展卡尔曼滤波器（EKF）辅助车载惯性测量单元（IMU）。在方向盘角度估计过程中，考虑并建模了可能影响方向盘角度精度的四个主要因素：车载IMU静态调平、方向盘倾斜角度、车辆加速度和车辆倾斜度。此外，还评估了这些因素对最终结果的影响。因此，提出了三种方向盘角度估计方法：无补偿法、部分补偿法和完全补偿法。使用Pixhawk（PX4）导航系统、iPad Air和OBD-II接口进行了道路实验测试。所提方法估计的航向变化的平均均方根误差（RMSE）为0.033弧度/秒。在不同GNSS信号中断期间，当使用航向和前进速度更新来辅助IMU时，估计了导航解决方案。与独立的IMU解决方案相比，将所提更新应用于导航滤波器时，在60秒和120秒的GNSS信号中断情况下，估计的导航解决方案分别提高了91%和97%。
