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The application of AR Model in magnetotelluric data processing

ZHANG Chun-hong,ZHANG Gang(Chengdu University of Technology,Key Laboratory of Earth Exploration and Information Technology,Chengdu 610059,China)  
In the magnetotelluric sounding raw data acquisition process,due to the influence of temperature,humidity,etc.of the instrument or the GPS satellite is abnormal,the collected time sequence data sometimes occur the phenomenon of frame skipping or deletion.To solve this problem,AR(p) prediction model is introduced to improve the utilization of magnetotelluric deep field observation data,proposing a new method to solve the problem of wild-collected data frame skipping or missing,and applied which into the measured long-period magnetotelluric data.The model order and the model parameters can be determined according to the known sequence,then the AR(p) prediction can be determined.the missing data in the magnetotelluric sounding raw data acquisition process can be predicted and filled to the corresponding position.And the spectrum of predicted data and that of the sample data are contrasted to show that AR(p) model can solve the discontinuity of the original data.this prediction method can make up for the deficiencies caused by the data collection process instrumentation hardware and improve the utilization of magnetotelluric sounding data.
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