Abstract
The performance of the Kalman Filter (KF) technique is most appropriate when both the process and observation are considered as white Gaussian noise. But in real time applications, this assumption is not always true. Two sorts of Kalman Filtering techniques i.e Augmented Kalman Filtering and Second Moment Information bases Kalman Filtering with colored system noise i.e (process noise and observation noise) are examined in this paper. Augmented Kalman Filtering (AKF) with colored measurement noise is shortly analyzed. Modified Kalman Filtering method (SMIKF) is proposed for colored process and observation noise. In order to check the performance of the system a real-time Mass-Spring Damper system having colored system noises is considered. The computational burdens of the proposed scheme is compared with AKF. The simulation results endorse the Performance of the suggested algorithm.
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