Radar backscatter modeling based on global TanDEM-X mission data

Abstract

Radar backscatter knowledge is a valuable input for many remote sensing applications, based on Synthetic Aperture Radar (SAR) systems. The amount of spaceborne data acquired within the TanDEM-X mission allows for the characterization of X-band backscatter on a global scale. The objective of this paper is to present a method for the characterization of radar backscatter behavior using a global statistical approach. The worldwide data set of images acquired within the TanDEM-X mission is taken into account, having the chance to exploit the unique high quality topography information associated to it. The input measurements are differently assessed, by using a qualitybased approach. A series of models can be derived, focusing on the backscatter dependency on polarization, incidence angle, ground classification, and seasonal time. The developed approach for the algorithm’s verification is presented as well, together with some preliminary results obtained from TanDEM-X mission data. The generation of up-to-date backscatter models for X-Band will provide a useful data base for the development of a large number of scientific applications and for the optimization of future radar systems.