基于无迹卡尔曼滤波的四旋翼无人飞行器姿态估计算法

Attitude Estimation Algorithm of Four Rotor Unmanned Aircraft Based on Unscented Kalman Filter

针对四旋翼无人飞行器姿态测量问题,提了一种基于无迹卡尔曼滤波的飞行器姿态估计算法.采用欧拉角法描述了飞行器的姿态解算模型,并在此基础上建立了飞行器的系统状态方程和观测方程;采用无迹卡尔曼滤波算法实现飞行器姿态角的解算.理论分析和仿真表明:与采用扩展卡尔曼滤波算法获得的飞行器姿态角信息相比较,虽然无迹卡尔曼滤波算法的计算时间稍有增加,但无迹卡尔曼滤波算法的计算精度和收敛速度比扩展卡尔曼滤波算法有显著的提高.

In order to resolve the problem of attitude estimation for four rotor unmanned aircraft,unscented kalman filter（UKF）attitude estimation algorithm was proposed.Firstly,Euler method was employed to describe the aircraft attitude solution model,and based on the solution model,the aircraft system state equation and observation equation were established.Secondly,UKF was used to obtain the attitude angles.The theory analysis and simulation results show that,compared with the spacecraft attitude angle information obtained by extended Kalman filter algorithm,although calculation time of UKF is slightly longer than that of extended kalman filter（EKF）,the calculation accuracy and convergence rate of UKF is significantly higher than that of EKF.