Remote Sensing

Remote sensing is an umbrella term for all methods, where, by measuring some signal, properties of the measured object are to be inferred.

Use cases encompass air surveillance and satellite-based exploration of Earth and other celestial bodies as well as tomographic methods in medicine.

The remote sensing group deals with state-of-the-art questions in signal processing of data collected by electromagnetic sounding. This involves research on novel and improvement upon existing methods to increase resolution and information retrieval, e.g. compressed sensing and synthetic aperture methods, as well as their implementation and evaluation.

In collaboration with industry and in international research projects, several direct and approximate numerical solvers for radar backscattering were designed and implemented, for example a Physical Optics based solver for radar backscattering of very large objects.

Focus is also put on the solution of inverse problems. A generic approach is the transformation of the inverse problem into an optimisation problem atop of the corresponding direct problem. In ongoing research projects, different forward solvers, such as FDTD, PSTD and MoMTD, were implemented. Problem-specific inversion strategies based on these solvers were already successfully applied.

Due to the huge requirements in computational resources, special attention is given to HPC adapted software engineering.