+1 862 207 3288 The Kalman Filter is an effective recursive filter that helps to estimate the internal state of the linear dynamic system that consists of a series of noisy measurements. It is used in wide range of engineering and econometric applications starting from radar to computer vision and in the estimation of structural macroeconomic models and in the field of control engineering. This filter has the ability to solve the linear-quadratic-gaussian control problem (LGQ). The kalman filter has the ability to act as a linear-quadratic regulator and as a controller and provides solutions to the most fundamental problems in the control theory.
In dempster-shafer theory, every state equation and observation is considered in a special case of a linear belief function and the kalman filter is a special case of combining linear belief functions into a join-tree or markov tree that is one of the common method. Additional approaches may include some of the belief filters that use bayes or evidential updations to state the equations. Various types of kalman filters are now developed such as square root filters and for the digital purpose like phase-locked loop, Frequency Modulation (FM), satellite communication and in other electronic communications equipment such as flip flops and registers.
