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在未知扰动噪声分布和强度先验信息前提下,提出了基于无迹卡尔曼滤波(UKF)状态估计的星敏感器和陀螺仪组合的高精度卫星姿态确定方法。设计了基于自回归(AR)模型的扰动噪声的建立方法,进而推导星敏感器与陀螺仪组合定姿的测量方程和过程方程,最终采用交互式多模型(IMM)定姿方法自适应调整模型集中不同噪声水平的概率以“高斯和”形式逼近未知的真实噪声,实现卫星高精度定姿。实验结果表明,IMM定姿精度优于单个模型定姿结果,并且具有较强的鲁棒性,能够为实际工程应用提供参考价值。
On the premise of unknown disturbance noise distribution and priori information of intensity, a high-precision satellite attitude determination method based on unscented Kalman filter (UKF) state estimation is proposed for star sensor and gyroscope combination. The method of establishing disturbance noise based on autoregressive (AR) model is designed, and then the measurement equation and process equation of combined star sensor and gyroscope are deduced. Finally, the IMM (Attitude Multi-model) method is used to adaptively adjust the model Probability of concentration of different noise levels approximates the unknown real noise in the form of “Gaussian and ” to achieve high-precision attitude determination of the satellite. The experimental results show that the IMM attitude and attitude accuracy is better than the single model attitude and pose, and has strong robustness, which can provide reference value for practical engineering applications.