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Kalman filter is often used tool for stochastic state estimation of a noisy system that is described by linear system and linear measurement model. It uses all it gets to make an overall best estimate of a state, i.e., the values of the variables of interest. It does not matter how accurate or precise the information is. It does this by incorporating knowledge about the system dynamics, statistical descriptions about the system dynamics, statistical descriptions of the system noise, measurementdoi:10.22214/ijraset.2019.4293 fatcat:iuwiykroe5gqjopr4u3pp62d44