An Interpolation Method for Data Containing Distortions and its Application to Aeromagnetic Data Preprocessing

Abstract

Nowadays, continuous sampling data have been widely used in the research field. However, many unpredictable distortion data points, caused by varying reasons, appear in the raw data randomly. Therefore, removing distortion data points are obligatory for raw data processing. The conventional method is the artificial recognition method, which has serious problems when applied to large volumes of data. Another way is the filtering method, which is limited by application conditions, has a bad influence on valid data what people do not expect. In this paper, we proposed an effective interpolation method to remove the distortion point. This method based on the assumption that changes between adjacent points in continuous sampling data are limited. The distortions can be recognized from the magnitude and the change rate and removed. At last, the polynomial interpolation method is used to obtain the final result. Such method has been used in the preprocessing of aeromagnetic data and gets a good result.