Abstract
The separate-bias estimation is well known for the unknown constant bias case. In this paper, the modified separate-bias Kalman filter is investigated for a continuous-time dynamical linear system in the presence of randomly time-varying bias. The certain general conditions are derived under which the modified separate-bias estimator is equivalent to the augmented state Kalman filter. However it can be shown that the resultant conditions for the continuous-time linear system with a stochastic bias are more complex than the discrete-time situation, and that the optimal separate-bias estimation may not provide any computational advantage.
