This paper examines one of the approaches to the challenge of estimating the values of the dynamic objects under changing environmental conditions. In most cases, the developers consider only fluctuation noises in order to simplify the systems of equations and increase the efficiency of the algorithms. Neglecting the current environment conditions can lead to data mismatch and even loss of control of the dynamic object. A simple method for detecting and reducing the systematic component of the error in the measurement process under external conditions (that significantly differ from laboratory ones) is proposed. The main goal of the authors was to find an algorithm for solving such problems with no loss in performance while estimating values. The results of measurements from heterogeneous sensors (processed with the proposed algorithm) may serve as a priori data for further processing or evaluation using any other method.