Unscented Kalman Filter Algorithm with Colored Noise and Its Application in Spacecraft Attitude Estimation

The accuracy and reliability of the estimation and prediction of satellite attitude are affected by not only the random noise and systematic errors, but also the colored noise related to time. Any theory or technique based on the hypothesis of Gaussian white noise ignoring the colored noise cannot guarantee the actual reliability of the parameter estimates. On the basis of Unscented Kalman Filter (UKF), the paper regards colored noise as pseudo white noise and considers colored noise as ARMA model, calculates its variance by polynomial-quotient which expresses colored noise model as form of progression. The random model can be corrected with this method. Then the new UKF is formulated by time series analysis theory. In order to verify the validity and rationality of this method, a simulated experiment is showed which validates that the method can restrain effectively the influence of colored noise for satellite attitude estimation.