北斗卫星与车载传感器融合的车辆定位

为了改善北斗卫星定位性能,基于卡尔曼滤波设计了北斗卫星与车载传感器的数据融合算法。算法包括车辆方向融合和车辆位置融合两部分,前者融合电子罗盘和陀螺测量得到的北向角及其变化率,估算北向角的真实值;后者首先同步车速矢量与北斗卫星测量得到的车辆位置矢量,再根据融合结果估算车辆定位信息。为了验证数据融合算法,设计了北斗卫星与车辆状态信息采集系统,利用本系统采集的实车数据进行的仿真计算表明,算法能够提高定位频率、减小定位误差,提高北斗卫星定位的性能。

Vehicle Positioning by Beidou Satellite Fusing with On-board Sensors

In order to improve the positioning performance of the Beidou satellite,an algorithm of data fusion between Beidou satellite and on-board sensors in vehicle is proposed based on Kalman filter.The algorithm consists of two parts: vehicle direction fusion and vehicle position fusion.The former estimates the real value of the north angle by fusing the north angles and its changing rates from both the electronic compass and gyroscope.The latter estimates the vehicle position by synchronizing the speed vector and the position vector measured by Beidou system.An information acquisition system for Beidou and vehicle states is designed to verify the data fusion algorithm.The results of simulative calculation show that the algorithm can increase the frequency, reduce the error,and improve the performance of the vehicle positioning by Beidou satellite.