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The estimation of the state of dynamic stochastic systems using the methods of filtration theory assumes the exact a priori setting of the parameters of the equation of the system and the probabilistic characteristics of its noises, which in practice are known approximately or change in time randomly. In this regard, the algorithm of adaptive estimation of one of the most critical parameters of the discrete stochastic filter - the dispersion matrix of noises acting on the system is considered for measuring and information systems that use, in addition to continuous noisy observations, also accurate observations at random times. The advantage of the proposed algorithm is the possibility of analytical determination of this dispersion matrix based on current precise observations and, as a consequence, a significant increase in the overall accuracy of the evaluation of the perturbed state vector of the system. A numerical example illustrating the possibility of effective practical use of the developed algorithm is given