There is proposed the sequential procedure for estimating of parameter ƒ in the model 1 1, n n n x a x + + = + ƒ + ƒ 0 n ≥. Here a is a noisy parameter. Random variables n ƒ are assumed to be independent with zero mean and unit variance. By appropriate choice of the parameters of procedure one can guarantee the precise quality of estimators in mean square sense. Some known algorithms can be applied to estimate a and ƒ. The problem is that using of known procedures might demand a great number of observations to guarantee the quality in the case of nonzero a. In contrast to the known ones the proposed procedure doesnt depend on the value of noisy parameter a. The main idea is to use the current estimator of noisy parameter for excluding it from equation (1). By making use of least squares method with special choice of auxiliary sequence of numbers the estimator with guaranteed quality is constructed. The obtained results are illustrated by numerical modeling.

Предложена модификация последовательной процедуры оценивания параметра процесса авторегрессии первого порядка при наличии мешающего параметра. При соответствующем выборе параметров процедура гарантирует заданную точность оценивания. Полученные результаты подтверждены результатами численного моделирования.