Spacecraft attitude estimation based on matrix Kalman filter and recursive cubature Kalman filter

作者：Zhang, Tao; Xu, Xiang^*; Wang, Zhicheng

来源：Proceedings of the Institution of Mechanical Engineers - Part G: Journal of Aerospace Engineering , 2018, 232(16): 3024-3033.

DOI：10.1177/0954410017723359

• Spacecraft attitude estimation
• matrix Kalman filter
• recursive cubature Kalman filter
• vector observation
• star sensor
• inertial navigation system

An interlaced matrix Kalman filter, which is based on vector observations and gyro measurements, is proposed for spacecraft attitude estimation in this paper. It combines the matrix Kalman filter and cubature Kalman filter to estimate spacecraft attitude and gyro drift bias, respectively. The defects of the original matrix Kalman filter, which could only estimate the attitude parameters of spacecraft, are addressed by the proposed interlaced matrix Kalman filter. In addition, the dimensions of cubature Kalman filter for conventional attitude estimation method are reduced by the designed recursive algorithm. It is noted that the two filters are not independent with each other. Firstly, the attitude quaternion of spacecraft is estimated by the modified matrix Kalman filter. Then, the estimated quaternion is input for the recursive cubature Kalman filter, which is used to estimate the gyro drift bias. Finally, the estimated gyro drift bias is compensated for the measurements of the gyros. Therefore, the precision of the estimated attitude of spacecraft is improved by the interacting process of the modified matrix Kalman filter and recursive cubature Kalman filter. A simulation test is designed to verify the advantage of the proposed method by comparing with the previous method, and the results indicate that the proposed algorithm has better performance on convergence rate and stability.

• 出版日期2018-12
• 单位南京信息工程大学; 东南大学