Kalman Filter and Its Application in Time Series Forecasting
Haichao Zheng · Keisou gijutsu · 2010
Considering the characteristics and requirements of fault forecasting,the deficiencies of traditional forecast methods were pointed out.The method that applies Kalman Filter in time series forecasting was put forward.The method for estimating parameters of ARMA(autoregressive moving average) based on Kalman Filter was introduced.Components of the model were analyzed with PSD(power spectrum density).The theory above was demonstrated through the modeling of random drift for FOG(fiber optic gyro).