Christian Wielenberg is a research scientist at Fraunhofer IIS in Nuremberg, where he pursues a PhD on Structured Signal Separation. He received his Bachelor’s degree in computer science from Otto von Guericke University Magdeburg and his Master’s degree in computer science from Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). His Master’s thesis on GNSS jammer localization using deep learning was conducted in cooperation with Fraunhofer IIS.
Research interests:
- RF Signal Processing
- GNSS
- Wireless Communications
- Bayesian Inference
Publications
Attention-based Fusion of IQ and FFT Spectrograms with AoA Features for GNSS Jammer Localization
We propose an approach for detecting and classifying interference while estimating the distance, azimuth, and elevation of jamming sources. We evaluate 128 vision encoder and time-series models to identify the highest-performing methods for each task and introduce an attention-based fusion framework that integrates in-phase and quadrature (IQ) samples with Fast Fourier Transform (FFT)-computed spectrograms while incorporating 22 AoA features
to enhance localization accuracy.