Projects

  • CATHLIN - A Conservative Likelihood Framework for Nonlinear Signal Processing (2016 - 2018)
    The analysis of nonlinear stochastic systems forms a challenge in various branches of science like physics, biology, and computer science. In particular in engineering, where increasing demands for low-cost, energy-efficient and fast sensing devices are emerging, and systems have to be operated outside linear regimes, nonlinear models have gained attention. Recent results for wireless systems show that the analog measurement equipment can be significantly simplified if one allows for highly nonlinear behavior and compensates the effects by optimized system design and strong statistical algorithms. However, to obtain high-resolution measurement systems under these circumstances, a mathematical framework is required to perform the transition from the output of a nonlinear and noisy physical system to an appropriate parametric probabilistic model. Approximating the system output by an exponential family distribution has shown to form a versatile method within the setting of parameter estimation with nonlinear system design. Therefore, the project aims at a better theoretical understanding of model replacement strategies and possible applications in wireless systems, biomedical engineering, and machine learning. (Project Institutions: Vrije Universiteit Brussel, Universität Bayreuth; Funding: European Union, Bundesministerium für Bildung und Forschung; Role: Principal Researcher)

  • SAMURAI - Sensor Array Processing for Multipath and Radio Interference Identification and Suppression (2011 - 2014)
    For safety-critical applications based on Global Satellite Navigation Systems (GNSS) accurate and reliable time-delay estimation needs to be ensured. Therefore, it is important to develop powerful methods for highly accurate synchronization of navigation receivers, even under difficult reception conditions. The use of array antennas together with appropriate signal processing methods, such as adaptive digital beam-forming or high resolution parameter estimation methods, has been proven to be one of the key technologies for an effective and highly reliable suppression of multipath and radio interference. SAMURAI can be summarized in three activities: development of signal processing, development of implementation concepts and testing under realistic conditions. (Project Institutions: Technische Universität München, Rheinisch-Westfälische Technische Hochschule Aachen, Deutsches Zentrum für Luft- und Raumfahrt; Funding: Bundesministerium für Wirtschaft und Energie; Role: Researcher)