In 1960, R.E. Kalman published his famous paper describing a recursive solution to the discrete-data linear filtering problem. Since that time, due in large part to advances in digital computing, the Kalman filter has been the subject of extensiv

Object-based framework for performing Kalman filtering for discrete time systems or continuous-discrete hybrid systems. Includes code for the classical Kalman filter for linear systems, the extended Kalman filter (EKF), and the more recent unscented

THIS PROGRAM IS FOR IMPLEMENTATION OF DISCRETE TIME PROCESS KALMAN FILTER FOR GAUSSIAN AND LINEAR STOCHASTIC DIFFERENCE EQUATION.

This paper is concerned with the minimum variance unbiased (MVU) finite impulse response (FIR) filtering problem for linear system described by discrete time-variant state-space models. An MVU FIR filter is derived by minimizing the variance the