GNSS Spoofing Detection and Exclusion by Decomposition of Complex Cross Ambiguity Function (DCCAF) with INS Aiding

Sahil Ahmed, Samer Khanafseh, Boris Pervan
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Abstract

In this paper, we present a methodology for detecting and excluding spoofed Global Navigation Satellite System (GNSS) signals by decomposing Complex Cross Ambiguity Functions (CCAF) into their constitutive components. Building on previous work in [1] and [2] utilizing CCAF decomposition and inverse Receiver Autonomous Integrity Monitoring (RAIM), we integrate CCAF decomposition with an inertial sensor in dynamic environments [3]. This integration enables us to identify and exclude spoofed signals, ensuring continuous tracking of the authentic signal for navigation. The method is effective in spoofing scenarios that can lead to Hazardous Misleading information (HMI) and are difficult to detect by other means. It can identify spoofing in the presence of multipath and when the spoofing signal is power-matched with offsets in code delay and Doppler frequency that are close to the true signal. Using the proposed approach, spoofing can be identified at an early stage within the receiver for dynamic users.
基于INS辅助的复杂交叉模糊函数分解的GNSS欺骗检测与排除
在本文中,我们提出了一种通过将复杂交叉模糊函数(CCAF)分解为其组成分量来检测和排除欺骗全球导航卫星系统(GNSS)信号的方法。在先前的研究[1]和[2]的基础上,我们利用CCAF分解和逆接收机自主完整性监测(RAIM),将CCAF分解与动态环境中的惯性传感器集成在一起[3]。这种集成使我们能够识别和排除欺骗信号,确保持续跟踪导航的真实信号。该方法在可能导致危险误导信息(HMI)且难以通过其他手段检测的欺骗场景中是有效的。该算法能够在多径存在和欺骗信号功率匹配且码延迟和多普勒频率偏移量接近真实信号的情况下识别欺骗信号。使用所提出的方法,可以在动态用户的接收器的早期阶段识别欺骗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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