A Research of Gyro/Star-Sensor Integrated Attitude Determination Based on Particle Filter

The improved particle filter is applied to satellite attitude determination of Gyro/Star-Sensor integrated system in this paper, including EKPF(Extended Kalman Particle Filter) and CKPF(Cubature Kalman Particle Filter). The improved filter uses EKF or CKF to generate sophisticated proposal distributions with the new observation in comparison to the general PF and it avoids the limitation of the EKF and the CKF which only apply to Gaussian distribution. The system models are established in which attitude quaternion and gyro bias are process parameter and outputs of star-sensors are measurement parameters. The results show that, by the suggested method, the rate of convergence is higher and the determination accuracy is improved, especially when the measurement noise is non-Gaussian.