Publication

Abstract : This paper focuses on the fractional-order Kalman filter’s growth, development, and application. Numerous advancement and the need for various application is critically investigated and summarized. The review work is done on fractional-order Kalman filters as they are best suited for constantly changing systems and can be used for estimating hidden variables. They provide the optimal solution to the filtering problem because it minimizes the state estimation error variance. They are also used to predict and update the location and velocity of an object given a video stream and detections on each of the frames. Many applications are described and analysed in the paper, including battery management, weather forecasting, stochastic state space systems, navigation of the system, and many others.