36 citations · 202 across the 35 of their papers we have counts for
5 papers · 1 filter
Attention-Based Fusion of IQ and FFT Spectrograms with AoA Features for GNSS Jammer Localization
Lucas Heublein, Christian Wielenberg, Thorsten Nowak +3
Jamming devices disrupt signals from the global navigation satellite system (GNSS) and pose a significant threat by compromising the reliability of accurate positioning. Consequent…
5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization
Nisha Lakshmana Raichur, Lucas Heublein, Christopher Mutschler +1
Indoor positioning based on 5G data has achieved high accuracy through the adoption of recent machine learning (ML) techniques. However, the performance of learning-based methods d…
Passive Channel Charting: Locating Passive Targets using a UWB Mesh
Raffael Poeggel, Maximilian Stahlke, Jonas Pirkl +4
Fingerprint-based passive localization enables high localization accuracy using low-cost UWB IoT radio sensors. However, fingerprinting demands extensive effort for data acquisitio…
Simplicity is Key: An Unsupervised Pretraining Approach for Sparse Radio Channels
Jonathan Ott, Maximilian Stahlke, Tobias Feigl +2
Unsupervised representation learning for wireless channel state information (CSI)reduces reliance on labeled data, thereby lowering annotation costs, and often improves performance…
VAE-based Feature Disentanglement for Data Augmentation and Compression in Generalized GNSS Interference Classification
Lucas Heublein, Simon Kocher, Tobias Feigl +3
Distributed learning and Edge AI necessitate efficient data processing, low-latency communication, decentralized model training, and stringent data privacy to facilitate real-time…