Research On Satellite Attitude Determination Algorithm Based On The Combination Of Star Sensor And Gyro

Satellite attitude determination is the key to control the satellite attitude and guarantee the stable operation of the satellite.In this paper,the attitude determination algorithm of satellite is investigated by using the configuration mode of attitude sensor with the combination of star sensor and gyro.Based on the nonlinear Kalman filter attitude determination algorithm based on the combination of star sensor and gyro,the corresponding optimization algorithm is proposed for the problem of unknown statistical characteristics of noise in the attitude determination system and the problem of sudden change of state in the process of attitude determination.The main research contents are as follows:(1)Based on the basic theory of satellite attitude determination,the EKF algorithm based on the combination of star sensor and gyro is designed to determine the attitude process.In order to avoid truncation errors,the CKF attitude calculation process based on quaternion and Rodrigues parameter conversion is designed,and the influence of attitude sensitive performance parameters on the attitude determination accuracy is studied.(2)To address the problem of unknown statistical characteristics of noise in the satellite attitude determination system,a Sage-Husa adaptive filter attitude determination algorithm is proposed on the basis of the CKF attitude determination algorithm,and the adaptive adjustment of the system filtering process is realized by online estimation of the system noise variance array Q and the measurement noise variance array R.According to the complex and changing working environment of the satellite attitude system,the optimization of finding the best forgetting factor and iterative estimation of R only is proposed to improve the filtering accuracy and reduce the computational burden.(3)To address the problem of sudden state changes encountered in the operation of the satellite attitude system,a strong tracking Cubature Kalman filter(STCKF)attitude determination algorithm based on multiple suboptimal fading factors is proposed by combining the CKF attitude determination algorithm with the strong tracking filter algorithm.Based on the optimization of the single fading factor,multiple suboptimal fading factors are designed to adjust the prediction error covariance matrix,and by adjusting different fading rates for different filter channels,the satellite attitude determination system is able to track fast in the face of sudden state changes.In this paper,a simulation experiment is carried out on the satellite attitude determination algorithm,The simulation results show that the optimized Sage-Husa attitude determination algorithm improves the filtering accuracy of the attitude determination system in the case of unknown statistical noise characteristics,and the optimized STCKF algorithm improves the stability of the attitude determination system in the case of abrupt state changes,which provides a theoretical reference for satellite attitude applications in aerospace engineering.