基于Gauss-Newton和UKF结合的微小卫星姿态确定算法

为提高微型低成本姿态敏感器的姿态确定精度，文章基于磁强计/太阳敏感器/陀螺的姿态敏感器配置，设计了高斯牛顿（Gauss-Newton，GN）迭代算法和无迹卡尔曼滤波（Unscented Kalman Filter，UKF）有机结合的微小卫星姿态确定算法，先用Gauss-Newton算法融合磁强计和太阳敏感器的数据，迭代计算最优四元数，然后以最优四元数联合陀螺数据作为观测量，以姿态四元数和惯性系下的角速度为状态量进行UKF，降低观测维数，并将观测方程转化为线性方程，显著减小计算量，同时克服了测量误差对姿态确定精度的影响。

Attitude determination algorithmfor micro-satellite based on Gauss-Newton and UKF

To improve the attitude determination accuracy of miniature low-cost attitude sensor, a micro-satellite attitude determination algorithm combining Gauss-Newton iterative algorithmandunscented Kalman filter (UKF) was designed based on the attitude sensor configuration of magnetometer/solar sensor/gyroscope. Firstly, the Gauss-Newton algorithm was used to fuse the data of magnetometer and solar sensor, and the optimal quaternion was obtained. Secondly, UKF was performed using the optimal quaternion combined with gyrodata as the observed data, using the attitude quaternions and the angularvelocity of theinertial systemas the state variables, and the observed dimension was reduced and the observation equation was transformed into a linear equation by this method. As a result, the computational complexity is significantly reduced and the influence of measurement error on attitude determination accuracy is overcomed.