基于对偶数和改进EKF的敏捷卫星姿态确定算法

针对对地观测敏捷卫星的大角度/位置的快速机动、高精度控制的任务需求，提出了一种敏捷卫星姿态确定算法。该算法利用对偶四元数推导出敏捷卫星运动学模型，并建立陀螺、星敏感器测量模型。通过对系统状态方程以及测量方程的线性化，应用自适应迭代扩展式卡尔曼滤波(adaptive iterated extended Kalman filer, AIEKF)算法对敏捷卫星的运动状态进行估计。仿真结果表明，所设计的算法能够有效估计系统状态噪声、测量噪声以及陀螺常值漂移，卫星的姿态角估计误差和角速度估计误差收敛至零，验证了算法的有效性。

Algorithm for agile satellite attitude estimation based on dual quaternion and improved EKF

In order to satisfy the agile satellite for earth observation with the ability of large-angle/large-position rapid maneuver and high-precision control performance, an algorithm for the agile satellite attitude estimation is presented. The kinematics equation of the agile satellite is derived based on the dual number. The gyro and star-sensor measurement models are proposed. By the linearization of the state and measurement equations, the adaptive iterated extended Kalman filter (AIEKF) is applied to estimate the attitude and attitude angular velocity of the agile satellite with the measurement data of the gyro and star-sensor. The simulation results demonstrate that the proposed algorithm can provide an effective estimation of the state noise, the observation noise, the gyro measurement noise, the attitude and attitude angular velocity of the agile satellite. Attitude determination of the agile satellite is completed in the attitude rapid maneuvering mode.