26 citations · 85 across the 28 of their papers we have counts for
16 papers · 1 filter
Analyzing and Characterizing Multi-Source Interference Effects at Jammertest Norway 2025
Lucas Heublein, Inigo Cortes Vidal, Tobias Feigl +2
Intentional radio-frequency interference from low-cost GNSS jammers increasingly threatens the accuracy and reliability of satellite-based positioning. Mitigating this threat requi…
The S-ICDF Dataset: Sionna-Simulated Dynamic Interference Characterization and Direction Finding
Christian Wielenberg, Lucas Heublein, Jonathan Ott +8
Jamming and spoofing threaten wireless and satellite navigation by disrupting or manipulating radio frequency (RF) signals, undermining availability, integrity, and trust. Robust i…
Active Sensing with Meta-Reinforcement Learning for Emitter Localization from RF Observations
M. Shamail J. Khan, Nisha L. Raichur, Lucas Heublein +5
Global navigation satellite system (GNSS) interference poses a serious threat to reliable positioning, especially in indoor and multipath-rich environments where source localizatio…
Resilient Channel Charting Under Varying Radio Link Availability
Jonas Pirkl, Jonathan Ott, Maximilian Stahlke +3
Channel charting (CC) has become a key technology for RF-based localization, enabling unsupervised radio fingerprinting, even in non line of sight scenarios, with a minimum of refe…
GNSS Jammer Direction Finding in Dynamic Scenarios Using an Inertial-based Multi-Antenna System
Lucas Heublein, Thorsten Nowak, Tobias Feigl +2
Jamming devices disrupt signals from the global navigation satellite system (GNSS) and pose a significant threat by compromising the reliability of accurate positioning. Consequent…
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…
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…
Achieving Generalization in Orchestrating GNSS Interference Monitoring Stations Through Pseudo-Labeling
Lucas Heublein, Tobias Feigl, Alexander Rügamer +1
The accuracy of global navigation satellite system (GNSS) receivers is significantly compromised by interference from jamming devices. Consequently, the detection of these jammers…
Radio Foundation Models: Pre-training Transformers for 5G-based Indoor Localization
Jonathan Ott, Jonas Pirkl, Maximilian Stahlke +2
Artificial Intelligence (AI)-based radio fingerprinting (FP) outperforms classic localization methods in propagation environments with strong multipath effects. However, the model…
Few-Shot Learning with Uncertainty-based Quadruplet Selection for Interference Classification in GNSS Data
Felix Ott, Lucas Heublein, Nisha Lakshmana Raichur +4
Jamming devices pose a significant threat by disrupting signals from the global navigation satellite system (GNSS), compromising the robustness of accurate positioning. Detecting a…
Velocity-Based Channel Charting with Spatial Distribution Map Matching
Maximilian Stahlke, George Yammine, Tobias Feigl +2
Fingerprint-based localization improves the positioning performance in challenging, non-line-of-sight (NLoS) dominated indoor environments. However, fingerprinting models require a…
Indoor Localization with Robust Global Channel Charting: A Time-Distance-Based Approach
Maximilian Stahlke, George Yammine, Tobias Feigl +2
Fingerprinting-based positioning significantly improves the indoor localization performance in non-line-of-sight-dominated areas. However, its deployment and maintenance is cost-in…
Towards Realistic Statistical Channel Models For Positioning: Evaluating the Impact of Early Clusters
Mohammad Alawieh, George Yammine, Ernst Eberlein +5
Physical effects such as reflection, refraction, and diffraction cause a radio signal to arrive from a transmitter to a receiver in multiple replicas that have different amplitude…
Complementary Semi-Deterministic Clusters for Realistic Statistical Channel Models for Positioning
Mohammad Alawieh, Ernst Eberlein, Stephan Jäckel +5
Positioning benefits from channel models that capture geometric effects and, in particular, from the signal properties of the first arriving path and the spatial consistency of the…
Position Tracking using Likelihood Modeling of Channel Features with Gaussian Processes
Sebastian Kram, Christopher Kraus, Tobias Feigl +3
Recent localization frameworks exploit spatial information of complex channel measurements (CMs) to estimate accurate positions even in multipath propagation scenarios. State-of-th…