基于传感器融合的车辆全球定位

Vehicle Global Positioning Based on Sensor Fusion

采用2个光学编码器作为当地传感器,1个GPS接收器作为全球传感器,GPS接收器和编码器组合成1对互补的传感器对来进行高精度的定位。传感器融合软件由2部分组成:基于车辆运动学的动态模型,用于结合GPS接收器和光学编码器;另一部分是用来整合传感器数据的随时间变化的卡尔曼滤波器。仿真和实验结果表明:提出的定位系统效果很好,可实时精确地预测车辆位置和方位角,GPS信号中混杂的噪声可消除80%。

Two optical encoders as local sensors and a GPS receiver as global sensor compose a complementary sensor pair for conducting high accuracy positioning. The software for sensor fusion consists of two parts ： a vehicle kinematics-based dynamic model to integrate GPS and optical encoders, and a time varying Kalman filter for fusing sensor data. Both simulations and experiments are carried out and the results show that the proposed positioning system works very well, being able to accurately estimate the position and heading angle of the vehicle real time with 80% of noise in GPS signal eliminated.