Interlaced matrix Kalman filter for spacecraft attitude estimation
A novel interlaced matrix Kalman filter (IMKF) is proposed in this study for spacecraft attitude estimation, which using vector observations and gyro measurements. It combines the matrix Kalman filter (MKF) and cubature Kalman filter (CKF) to estimate spacecraft attitude and gyro drift bias, this method overcomes the defects of the traditional MKF which could only estimate the attitude parameters of spacecraft, and also reduce the state dimension of CKF for spacecraft attitude estimation. The two filter are not independent each other, on the one hand, the attitude quaternion of spacecraft is estimated by modified MKF, and then the estimated quaternion is input for specific CKF which is used to estimate the gyro drift bias. Besides, the gyro drift bias which is estimated by CKF to calibrate the gyro measurement, and then the estimated attitude precision is improved under the proposed interlaced algorithm. A Monte Carlo simulation is designed in this paper, the simulated results of the IMKF are compared with the traditional method, which indicate that the proposed algorithm has better performance on convergence and stability.
2016 Integrated Communications Navigation and Surveillance (ICNS)