Investigation on filter method of FOG drift data based on ARIMA model
Guangfu Ma · Transducer and Microsystem Technologies · 2007
FOG drift data is validated to be a non-stationary time series and a ARIMA model is established.The FOG drift data is processed by using Kalman filter;and the filter results are analyzed and fitted by Allan variance analyzing method and least squares method.In addition,an AR model is discussed and compared with the ARIMA model.Experimental result shows that ARIMA model based Kalman filter is efficient in reducing the bias instability and angle random walk.