Development of Pugachev filtering for stochastic systems

Statistical methods of information processing (filtering, extrapolation, interpolation etc) in stochastic systems (StS) are the basis of modern statistical informatics. Analytical survey and main tendencies of nonlinear conditionally optimal Pugachev filters (PF) for StS are considered. Pugachev filters for regular and nonregular, continuous and discrete, Gaussian and non-Gaussian StS are discussed. Interconnection between PF and Kalman filters including various statistical criteria is given. Problems of joint filtering and recognition and PF trends are considered.