Optimal discrete interpolation with constant delay of samples of a discrete-continuous Markov process against a background of correlated Markov noise

The problem of synthesizing optimal and quasi-optimal algorithms for interpolation with constant delay of samples of continuous components of a vector discrete-continuous Markov random process is solved using the methods of the Markov theory of estimation of random processes, taking into account the known statistical characteristics of additive Markov correlated noise. The method of difference measurements was used in the synthesis of algorithms. The structural diagram of the quasi-optimal digital filter is given. A simple example using the method of simulation modeling shows the performance of the quasi-optimal algorithm in statistically uncertain situations when guiding the control object to a maneuvering air target.