基于改进型卡尔曼滤波的运动载体姿态估计

Attitude Estimation of Moving Carriers Based on Improved Kalman Filter

针对MEMS陀螺零偏导致运动载体姿态精度下降的问题,本文以MEMS惯性测量器件MPU6050为核心,提出了一种基于改进型卡尔曼滤波的姿态估计算法。采用欧拉角作为姿态解算的基础,通过惯性测量单元(IMU)测量运动载体的姿态数据,采用改进型卡尔曼滤波,对陀螺仪和加速度计数据进行融合,并实时估计陀螺零偏。实验结果表明,本文提出的算法能够获得较高精度的姿态信息,抑制MEMS陀螺零偏引起的姿态发散,可以准确地表示运动载体在静态和动态情况下的方位。

Aiming at the problems that the attitude precision of moving carriers is reduced due to the zero bias of MEMS gyroscope,this paper presents an attitude estimation algorithm based on improved Kalman filter,which is based on MEMS inertial measurement device MPU6050.Using Euler angles as the basis of attitude solution,the inertial measurement unit(IMU)is used to measure the attitude data of moving carriers,and the data of gyroscope and accelerometer are fused by improved Kalman filter,besides the zero bias of the gyroscope is estimated in real time.The experimental results show that the proposed algorithm can obtain the attitude information with high accuracy,suppress the attitude divergence caused by the zero bias of MEMS gyroscope,and accurately represent the orientation of the moving carriers under static and dynamic conditions.