一种基于Madgwick-EKF融合算法的卫星姿态测量方法  

A Satellite Attitude Measurement Method Based on the Madgwick-EKF Fusion Algorithm

作　　者：史炯锴 张松勇[1] 渐开旺[1] 高迪驹[1] SHI Jiongkai;ZHANG Songyong;JIAN Kaiwang;GAO Diju(Key Laboratory of Marine Technology and Control Engineering,Shanghai Maritime University,Shanghai 201306,China)

机构地区：[1]上海海事大学航运技术与控制工程交通运输行业重点实验室,上海201306

出　　处：《上海航天（中英文）》2024年第2期95-103,120,共10页Aerospace Shanghai（Chinese&English）

摘　　要：针对低地球轨道卫星姿态测量时,传感器易受噪声干扰、陀螺仪漂移等问题,提出一种基于Madgwick扩展卡尔曼滤波合算法(EKF)的卫星姿态测量方法。该方法采用陀螺仪、加速度计、磁强计等多传感器数据进行融合,并结合Madgwick算法和EKF算法的优点,实现姿态测量。首先,通过Madgwick算法,利用多个传感器测量数据计算初始姿态。然后,基于初始姿态和实际测量数据,应用EKF算法进行数据融合和噪声滤除,以获得最终准确的姿态估计。实验结果表明:相较Madgwick算法,本算法在测量精度上提升了65.8%,且具有较高的鲁棒性,为低地球轨道卫星姿态测量提供了一种有效的方案。In response to the issues such as sensor noise interference and gyroscope drift during the attitude measurement of low Earth orbit(LEO)satellites,a satellite attitude measurement method based on the Madgwick-extended Kalman filter(EKF)fusion algorithm is proposed.This method uses the data of multiple sensors,e.g.,gyroscopes,accelerometers,and magnetometers,for fusion,and leverages the advantages of both the Madgwick algorithm and the EKF algorithm to achieve attitude measurement.Initially,the Madgwick algorithm is used to calculate the initial attitude with the data measured by multiple sensors.Subsequently,based on the initial attitude and the measured data,the EKF algorithm is used for data fusion and noise filtering so as to obtain the final accurate attitude estimation.The experimental results indicate that compared with the Madgwick algorithm,the fusion algorithm improves the measurement accuracy by 65.8%,and exhibits high robustness.This method provides an effective solution for the attitude measurement of LEO satellites.

关 键 词：姿态测量 姿态传感器 Madgwick算法 扩展卡尔曼滤波 近地轨道卫星 

分 类 号：V448.22[航空宇航科学与技术—飞行器设计]