Метод адаптації експоненціального фільтра Брауна із використанням методу найменших квадратів

Proposed structure of the filtering algorithm gives an opportunity to avoid some of disadvantages of exponential smoothing. The main aim of proposed algorithm is to estimate filtration quality and get an ability to change smoothing factor during the work of the system. We used the method of least squares to estimate the difference between smoothed signal and signal that was built from filtered signal got by its approximation. This method might be used in the case if the trajectory of the tracking signal is not changing during the estimating process or it might be changed inconsiderably. This data processing algorithm can be used as filtering and forecasting system and integrated in systems with lags.