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20192026
most citedDomain Adaptation for Time-Series Classification to Mitigate Covariate Shift

36 citations · 178 across the 30 of their papers we have counts for

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10 papers · 1 filter

eess.SP2026

Permutation-Invariant Time-Frequency Segmentation and Parameter Estimation of Multiple Overlapping Interference Signals

Lucas Heublein, Christian Wielenberg, Christopher Mutschler +1

Radio-frequency interference threatens satellite navigation, wireless communications, radar, and industrial sensing. Reliable operation therefore requires spectrum situational awar…

eess.SP2026

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…

eess.SP2026

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…

eess.SP2026

Physics-Informed Domain-Invariant Feature Learning with Autoencoder-Driven Gaussian Clustering for Robust Non-line-of-Sight Scenarios

Nisha L. Raichur, Lucas Heublein, Dominik Seuß +2

Jamming and spoofing pose significant threats to wireless and satellite navigation by disrupting radio-frequency (RF) signals and compromising availability and integrity. Robust RF…

eess.SP2026

Receiver-Aware Analysis and Verification of the Spectral Separation Coefficient Under Interference-Induced Degradation

Lucas Heublein, Fabian Benschuh, Alexander Rügamer +1

Interference poses a significant challenge to satellite-based positioning systems, making it essential to accurately quantify the effects of specific interference types on receiver…

eess.SP2026

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…

eess.SP2025

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…

eess.SP2025★ 1 cited

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…

eess.SP2024★ 1 cited

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…

eess.SP2024★ 13 cited

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…