A method for Sentinel-1 DEM outlier removal using 2-D Kalman filter

Abstract

The generation of a very accurate and precise digital elevation model (DEM) is one of the main objectives of remote sensing applications. Synthetic-Aperture Radar (SAR) interferometry is one of the most common methods for DEM generation. Moreover, one of the most recent Sentinel-1 missions is SAR imagery. Sometimes due to a variety of errors such as interferogram phase error, DEMs based on SAR interferometry contain outliers in the elevation of points. Thus, they need to be modified and updated. In this study, a 2-D Kalman filter-based method is applied to remove outliers from DEM generated from Sentinel-1 images. The proposed method is examined over an area in Iran and the results are compared with a high resolution and precision DEM. The results demonstrate that the efficiency of the proposed method in the outlier removal and root mean square error (RMSE) of the DEM is improved from 11% to 17%.