基于MME准则估计卫星姿态的非线性滤波算法

结合矢量观测的特点，基于最小模型误差准则给出了一种确定卫星姿态的实时估计算法，称为预测滤波算法。该算法利用矢量观测信息，对动力学方程中的力矩模型误差进行预测，并利用预测值修正动力学模型，从而准确地估计卫星的三轴运动姿态，同时能获得角速度估计值。通过误差观测矢量的建立，进一步提出了能够简化准则函数的修正预测滤波算法。仿真结果证明，预测滤波算法及其修正算法克服了扩展卡尔曼滤波器的不足，能够有效地解决存在显著模型误差情况下的非线性估计问题。

Nonlinear predictive filter for satellite attitude estimation based on MME criterion

Considering the character of vector observation, a real time predictive filter based on minimum model error (MME) criterion is presented for satellite attitude estimation. Using vector measurements, the filter predicts torque modeling errors in the dynamics equation one time step ahead, then the dynamics model is corrected by the predicted value, consequently the satellite attitude can be estimated accurately and the angular rate estimate is obtained also. By the definition of error observation vector, the modified predictive algorithm that simplifies criteria function is also derived. The predictive filter and the modified one overcome the shortcomings of the EKF filter, they can effectively solve nonlinear estimation problems in the presence of significant model error. Both feasibility and high performance of the predictive filter and the modified one is demonstrated by simulation test.