Summary
International Conference on Emerging Technologies for Communications
2022
Session Number:O3
Session:
Number:O3-5
GNSS Spoofing Detection using Multiple Sensing Devices and Decision Tree Classifier
Xin Qi, Toshio Sato, Zheng Wen, Masaru Takeuchi, Yutaka Katsuyama, Kazuhiko Tamesue, Kazue Sako, Jiro Katto, Takuro Sato,
pp.-
Publication Date:2022/11/29
Online ISSN:2188-5079
Summary:
For next-generation logistics systems using autonomous vehicles and drones, spoofing of the GNSS location data induces serious problems. Although signal-based anti-spoofing has been studied, it is difficult to apply to current commercial GNSS modules in many cases. We investigate possibilities to detect spoofing of GNSS location data using multiple sensing devices and a decision tree classifier. Multiple features using the GNSS, beacons, and the IMU are defined and create a model to detect spoofing. Experimental results using learning-based classifier indicates the higher performances and generalization capability. The results also show that distance from beacons is useful to detect GNSS spoofing and indicate prospects of installation for the future drone highways.