Abstract
This paper provides a new method for robust spacecraft attitude estimation in the presence of constant and but unknown measurement biases. The proposed method is developed based on the separate-bias or two-state Kalman filter which was first introduced by Friedland. The separate-bias Kalman filter consists of two stages: the nrst stage, the "bias-free" filter, is based on the assumption that the bias is nonexistent; the second stage, the "bias" filter, produces an estimate of the bias vector. The output of the first filter is then corrected with the output of the second filter. In this research, the authors propose an adaptive calculation of the Kalman gain inside the "bias" filter in order to improve the convergence speed, robustness when the estimator works with larger initial errors. Moreover, the research also provides analysis and comparison between proposed method with original separate-bias filter, unscented Kalman filter and extended Kalman filter based on the results of several numerical simulation scenarios about spacecraft attitude estimation.
