Generation of Large-Scale High Quality 3-D Urban Models

Abstract

Interferometric synthetic aperture radar (InSAR) techniques are powerful tool for reconstructing the 3-D position of scatterers, especially for the urban areas. Since the estimation accuracy depends on the inverse of number of interferograms and signal-to-noise ratio (SNR), it is necessary to use as many as possible interferograms in order to achieve more accurate result. However, the number of interferograms of TanDEM-X data is generally limited for most areas. Therefore, in order to maintain the estimation accuracy, one feasible way is to increase the SNR. In this work, we proposed a novel framework, which integrates the non-local procedure into SAR tomography inversion and combines the robust estimation. A large-scale demonstration has been carried out with five TanDEM-X bistatic data, which covers the entire city of Munich, Germany. Quantitative evaluation of the reconstructed result with the LiDAR reference exhibits the standard deviation of the height difference is within two meters, which implies the proposed framework has great potential for high quality large-scale 3-D urban modeling.