GPS/速率陀螺组合Kalman滤波姿态确定算法研究

建立了GPS／速率陀螺组合姿态估计系统的模型，研究比较了三种典型的Kalman滤波姿态确定算法：状态扩充法、量测量求差法和时变噪声估计跟踪自适应滤波算法。给出了某航天器采用GPS／速率陀螺组合姿态确定的仿真计算结果，并对结果进行了分析。结果表明，与传统Kalman滤波算法比较，时变噪声跟踪自适应滤波算法和量测量求差滤波算法能较好地消除GPS测量中相关时变噪声的影响，提高姿态确定的精度；而且时变噪声跟踪自适应滤波算法能很好地消除由于噪声统计性能的不确定性对Kalman滤波的影响，提高姿态确定系统的性能。

Study of kalman filtering attitude determination algorithms for GPS/Rate gyro integrated system

GPS/rate gyro integrated attitude determination system,a typical spacecraft attitude determination scheme which uses the measurement information from GPS,rate gyro and spacecraft attitude dynamics to estimate the attitude information and measurement errors of GPS and gyro by filtering algorithms,has the characteristics of high accuracy,good reliability and low cost.In this paper,the models for GPS/rate gyro integrated attitude determination system are established.Three Kalman filtering algorithms including state augment,measurement difference and adaptive Kalman filtering method are given and analyzed.An adaptive Kalman filtering algorithm,which has the characteristic of time varied noise statistic following and estimation,is presented.Simulation results of GPS/rate gyro integrated attitude determination system using these algorithms are carried out and analyzed.Compared with the traditional Kalman filtering algorithm,both the adaptive Kalman filtering algorithm and the measurement difference algorithm can reduce the influence of time varied measurement noise and improve the accuracy of attitude determination,and the adaptive Kalman filter can also mitigate the effect of the uncertainly of noise statistic on Kalman filter,which improves the performance of the attitude determination system.