当前位置: X-MOL 学术Int. J. Satell. Commun. Netw. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Global Navigation Satellite Systems Spoofing Detection through measured Autocorrelation Function Shape Distortion
International Journal of Satellite Communications and Networking ( IF 0.9 ) Pub Date : 2021-09-01 , DOI: 10.1002/sat.1425
Abdul Malik Khan 1 , Attiq Ahmad 1
Affiliation  

With the expansion in Global Navigation Satellite System (GNSS) constellations and emerging applications utilizing GNSS systems, the issue of detection of interference is evolving as a growing concern in the satellite navigation user community. Threats for GNSS users can be classified as unintentional interference, jamming, and spoofing. Spoofing is more harmful among them because the target receiver might not be aware of the attack and, as a consequence, generate misleading position information. Spoofing attacks are classified as simplistic, intermediate, and sophisticated depending on their complexity of implementation. We focused primarily on the detection of intermediate spoofing attacks by measuring shape distortion (SD) through multiple correlators that cover multiple chips around the prompt tracking point. The SD metric compares the measured and typical values of the autocorrelation function and decides on the spoofing using a noise variance based threshold. The proposed SD metric is found to be very effective in detecting the spoofing attack during the pull-off phase of the attack. The method is verified through simulations, synthetic spoofing data, and the TEXBAT data shared by the University of Texas, Austin. Different formulations of the proposed method are compared to provide an optimal number of correlator taps in each channel.

中文翻译:

通过测量的自相关函数形状失真进行全球导航卫星系统欺骗检测

随着全球导航卫星系统 (GNSS) 星座的扩展和使用 GNSS 系统的新兴应用,干扰检测问题正在演变为卫星导航用户社区日益关注的问题。GNSS 用户面临的威胁可分为无意干扰、干扰和欺骗。欺骗在其中危害更大,因为目标接收者可能不知道攻击,因此会产生误导性的位置信息。欺骗攻击根据其实现的复杂性分为简单型、中等型和复杂型。我们主要专注于通过覆盖快速跟踪点周围多个芯片的多个相关器测量形状失真 (SD) 来检测中间欺骗攻击。SD 度量比较自相关函数的测量值和典型值,并使用基于噪声方差的阈值来决定欺骗。发现所提出的 SD 度量在攻击的拉断阶段检测欺骗攻击非常有效。该方法通过模拟、合成欺骗数据和德克萨斯大学奥斯汀分校共享的 TEXBAT 数据进行了验证。比较了所提出方法的不同公式,以在每个通道中提供最佳数量的相关器抽头。以及德克萨斯大学奥斯汀分校共享的 TEXBAT 数据。比较了所提出方法的不同公式,以在每个通道中提供最佳数量的相关器抽头。以及德克萨斯大学奥斯汀分校共享的 TEXBAT 数据。比较了所提出方法的不同公式,以在每个通道中提供最佳数量的相关器抽头。
更新日期:2021-09-01
down
wechat
bug