基于扩展Kalman滤波的无人驾驶车姿态测量研究

Research on Attitude Measurement of Unmanned Vehicle Based on Extended Kalman Filter

针对一般传感器精度低而高精度传感器成本高的问题,提出了基于扩展Kalman滤波的无人驾驶车姿态解算的测量算法,该算法产生了姿态测量的线性最小均方误差估计,可以在线对无人驾驶车行驶过程中的噪声进行估计,使得误差降低。Matlab仿真结果说明了该算法的有效性,为无人驾驶车的姿态参数测量提供了研究思路,具有一定的价值。

Aiming at the problem that the general sensor has low precision and high-precision sensor cost,this paper proposes a measurement algorithm based on extended Kalman filter for the attitude calculation of driverless vehicles.The algorithm generates linear minimum mean square error estimation of attitude measurement,which can be online.The noise during driving the driverless car is estimated,so that the error is reduced.The Matlab simulation results show the effectiveness of the algorithm provides the research on the attitude parameter measurement of the driverless car,which has certain value.