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Integration of algebraic method and EKF for attitude determination of small information satellites

机译:代数方法与EKF的集成用于确定小型信息卫星的姿态

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In this study an integrated Algebraic method/ Extended Kalman fitler (EKF) attitude determination system is presented, in which the 2-vector and EKF algorithms are combined to estimate the attitude angles and angular velocities. As a reference directions for algebraic method, the unit vectors toward the Sun and Earth's Magnetic Field are used. The Euler angles produced 2-vector algorithm and their error variances are provided as input to the EKF. Then the EKF uses this attitude information as the measurements for providing more accurate attitude estimates even when the satellite is in eclipse. The “attitude angle error covariance matrix” calculated for the estimations of the algebraic method are regarded as the measurement noise covariance for the EKF. The parameters of satellite's rotational motion (Euler angles and angular velocities) are estimated using EKF. In comparison to more traditional approaches, this preprocessing step significantly reduces the complexity of filter design by allowing the use of linear measurement equations.
机译:在这项研究中,提出了一个集成的代数方法/扩展卡尔曼拟合器(EKF)姿态确定系统,其中结合了2矢量和EKF算法来估计姿态角和角速度。作为代数方法的参考方向,使用了朝向太阳和地球磁场的单位矢量。欧拉角产生的2矢量算法及其误差方差作为输入提供给EKF。然后,EKF使用此姿态信息作为测量值,即使卫星处于日食时也可提供更准确的姿态估计。计算用于代数法估计的“姿态角误差协方差矩阵”被视为EKF的测量噪声协方差。卫星的旋转运动参数(欧拉角和角速度)使用EKF进行估算。与更传统的方法相比,该预处理步骤允许使用线性测量方程,从而大大降低了滤波器设计的复杂性。

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