FelixOtt/gnss_few-shot_learning

Few-Shot Learning with Uncertainty-based Quadruplet Selection for Interference Classification in GNSS Data

Latest update: 2024-10-30

Introduction

Create a conda environment with the wheel environment.yml. Helper functions are included in the file utilities.py. The source code contains Python files for few-shot learning. Therefore, run the files train_episodic.py and test_episodic.py. For simple post-training, i.e., fine-tuning for each class incrementally, use the files post_train_episodic.py" and "post_test_episodic.py.

Uncertainty: Train the models in consecutive orders (--run_num) for the correct numbering for the uncertainty evaluation based on Deep Ensembles (see Lakshminaranayan et al.). Our code contains uncertainty.py to calculate the uncertainty based on uncertainty decomposition (Kwon et al.).

Our source code for few-shot learning is based on the repository: easy-few-shot-learning (https://github.com/sicara/easy-few-shot-learning)

Dataset

Download the spectrum highway dataset 1 recorded on a German highway from the following website: https://gitlab.cc-asp.fraunhofer.de/darcy_gnss/FIOT_highway

For our spectrum highway dataset 2 recorded along a different highway bridge, see the following website: https://gitlab.cc-asp.fraunhofer.de/darcy_gnss/fiot_highway2

For our dataset recorded in a controlled environment with a high-frequency antenna, see the following website: https://gitlab.cc-asp.fraunhofer.de/darcy_gnss/FIOT_LC_laboratory

For our dataset recorded in a controlled environment with a low-frequency antenna, see the following website: https://gitlab.cc-asp.fraunhofer.de/darcy_gnss/controlled_low_frequency

References

For more information of our method, the dataset, and results, see our publication. If you use our method or dataset for your research, please consider citing:

@inproceedings{ott_heublein_icl,
  author = {Felix Ott and Lucas Heublein and Nisha Lakshmana Raichur and Tobias Feigl and Jonathan Hansen and Alexander Rügamer and Christopher Mutschler},
  title = {{Few-Shot Learning with Uncertainty-based Quadruplet Selection for Interference Classification in GNSS Data}},
  booktitle = {\href{https://ieeexplore.ieee.org/document/10578525}{Intl. Conf. on Localization and GNSS (ICL-GNSS)}},
  month = jun,
  year = {2024},
  address = {Antwerp, Belgium},
  doi = {10.1109/ICL-GNSS60721.2024.10578525}
}

Acknowledgment

This work has been carried out within the DARCII project, funding code 50NA2401, supported by the German Federal Ministry for Economic Affairs and Climate Action (BMWK), managed by the German Space Agency at DLR and assisted by the Bundesnetzagentur (BNetzA) and the Federal Agency for Cartography and Geodesy (BKG).

License

This work is licensed under a Creative Commons Attribution 4.0 International License, see http://creativecommons.org/licenses/by/4.0/

Kontakt

If you have any questions or tips to improve the datasets, contact us:

Felix Ott: felix.ott@iis.fraunhofer.de

Lucas Heublein: lucas.heublein@iis.fraunhofer.de

Nordostpark 84, 90411 Nürnberg, Germany, GoogleMaps

Fraunhofer Institute for Integrated Circuits IIS, Nürnberg, Germany