FIELD: adaptive systems.
SUBSTANCE: invention relates to the field of adaptive systems. To achieve the effect, a method for adaptive filtering is proposed, in which the Kalman filtering of the state vector of the observed object is carried out in the presence of current discrete noisy measurements. Wherein the dispersion matrix of object disturbances is determined by using the transition matrix of the system state, the measurement matrix, the covariance matrix, the transposed transition matrix of the system state, the transposed measurement matrix and the inverse dispersion matrix of measurement noise, after which the Kalman filtering of the state vector of the observed object is carried out according to the current discrete noisy measurements with the newly formed dispersion matrix of plant disturbances until the next accurate measurements arrive, after which the adaptive filtering procedure is repeated.
EFFECT: ensuring stability and improving the accuracy of Kalman filtering.
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