A GNSS Spoofing Detection and Direction-Finding Method Based on Low-Cost Commercial Board Components
2023
Pengrui Mao | Hong Yuan | Xiao Chen | Yingkui Gong | Shuhui Li | Ran Li | Ruidan Luo | Guangyao Zhao | Chengang Fu | Jiajia Xu
The Global Navigation Satellite System (GNSS) is vulnerable to deliberate spoofing signal attacks. Once the user wrongly locks on the spoofing signal, the wrong position, velocity, and time (PVT) information will be calculated, which will harm the user. GNSS spoofing signals are difficult to carry out spoofing attacks in the direction of arrival (DOA) of the real signal, so the spoofing detection method based on DOA is very effective. On the basis of identifying spoofing signals, accurate DOA information of the signal can be further used to locate the spoofer. At present, the existing DOA monitoring methods for spoofing signals are mainly based on dedicated antenna arrays and receivers, which are costly and difficult to upgrade and are not conducive to large-scale deployment, upgrade, and maintenance. This paper proposes a spoofing detection and direction-finding method based on a low-cost commercial GNSS board component (including an antenna). Based on the traditional principle of using a multi-antenna carrier phase to solve DOA, this paper innovatively solves the following problems: the poor direction-finding accuracy caused by the unstable phase center of low-cost commercial antennas, the low success rate of spoofing detection in a multipath environment, and the inconsistent sampling time among multiple low-cost commercial GNSS boards. Moreover, the corresponding prototype equipment for spoofing detection and direction-finding is developed. The measured results show that it can effectively detect spoofing signals in open environments. Under a certain false alarm rate, the detection success rate can reach 100%, and the typical direction-finding accuracy can reach 5°:.
Показать больше [+] Меньше [-]Ключевые слова АГРОВОК
Библиографическая информация
Эту запись предоставил Multidisciplinary Digital Publishing Institute