Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Feigl, Tobias"'
Artificial Intelligence (AI)-based radio fingerprinting (FP) outperforms classic localization methods in propagation environments with strong multipath effects. However, the model and data orchestration of FP are time-consuming and costly, as it requ
Externí odkaz:
http://arxiv.org/abs/2410.00617
Autor:
Heublein, Lucas, Feigl, Tobias, Nowak, Thorsten, Rügamer, Alexander, Mutschler, Christopher, Ott, Felix
Jamming devices present a significant threat by disrupting signals from the global navigation satellite system (GNSS), compromising the robustness of accurate positioning. The detection of anomalies within frequency snapshots is crucial to counteract
Externí odkaz:
http://arxiv.org/abs/2409.15114
Autor:
Raichur, Nisha L., Heublein, Lucas, Feigl, Tobias, Rügamer, Alexander, Mutschler, Christopher, Ott, Felix
The primary objective of methods in continual learning is to learn tasks in a sequential manner over time from a stream of data, while mitigating the detrimental phenomenon of catastrophic forgetting. In this paper, we focus on learning an optimal re
Externí odkaz:
http://arxiv.org/abs/2405.11067
Autor:
Ott, Felix, Heublein, Lucas, Raichur, Nisha Lakshmana, Feigl, Tobias, Hansen, Jonathan, Rügamer, Alexander, Mutschler, Christopher
Publikováno v:
IEEE 2024 International Conference on Localization and GNSS (ICL-GNSS)
Jamming devices pose a significant threat by disrupting signals from the global navigation satellite system (GNSS), compromising the robustness of accurate positioning. Detecting anomalies in frequency snapshots is crucial to counteract these interfe
Externí odkaz:
http://arxiv.org/abs/2402.09466
Autor:
Stahlke, Maximilian, Yammine, George, Feigl, Tobias, Eskofier, Bjoern M., Mutschler, Christopher
Fingerprint-based localization improves the positioning performance in challenging, non-line-of-sight (NLoS) dominated indoor environments. However, fingerprinting models require an expensive life-cycle management including recording and labeling of
Externí odkaz:
http://arxiv.org/abs/2311.08016
Autor:
Stahlke, Maximilian, Yammine, George, Feigl, Tobias, Eskofier, Bjoern M., Mutschler, Christopher
Fingerprinting-based positioning significantly improves the indoor localization performance in non-line-of-sight-dominated areas. However, its deployment and maintenance is cost-intensive as it needs ground-truth reference systems for both the initia
Externí odkaz:
http://arxiv.org/abs/2210.06294
Autor:
Ott, Felix, Raichur, Nisha Lakshmana, Rügamer, David, Feigl, Tobias, Neumann, Heiko, Bischl, Bernd, Mutschler, Christopher
Visual-inertial localization is a key problem in computer vision and robotics applications such as virtual reality, self-driving cars, and aerial vehicles. The goal is to estimate an accurate pose of an object when either the environment or the dynam
Externí odkaz:
http://arxiv.org/abs/2208.00919
Autor:
Alawieh, Mohammad, Eberlein, Ernst, Jäckel, Stephan, Franke, Norbert, Ghimire, Birendra, Feigl, Tobias, Yammine, George, Mutschler, Christopher
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 propagation condition of multiple links. The models that capture the
Externí odkaz:
http://arxiv.org/abs/2207.07837
Autor:
Alawieh, Mohammad, Yammine, George, Eberlein, Ernst, Ghimire, Birendra, Franke, Norbert, Jäckel, Stephan, Feigl, Tobias, Mutschler, Christopher
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 and rotation. Bandwidth-limited signals, such as positioning reference
Externí odkaz:
http://arxiv.org/abs/2207.07838
Autor:
Kram, Sebastian, Kraus, Christopher, Feigl, Tobias, Stahlke, Maximilian, Robert, Jörg, Mutschler, Christopher
Recent localization frameworks exploit spatial information of complex channel measurements (CMs) to estimate accurate positions even in multipath propagation scenarios. State-of-the art CM fingerprinting(FP)-based methods employ convolutional neural
Externí odkaz:
http://arxiv.org/abs/2203.13110