使用辅助传感器进行GNSS攻击检测的可信导航算法

直达链接：https://doi.org/10.3390/app12031386

GNSS Spoofing Identification and Smoothing Localization Method for GNSS/Visual SLAM System

翻译：GNSS/视觉SLAM系统中的GNSS欺骗识别与平滑定位方法

Abstract
A smoothing localization method for Global Navigation Satellite System (GNSS) and visual Simultaneous Localization and Mapping (SLAM) system is proposed to identify GNSS spoofing, optimize the cumulative error of the GNSS/visual SLAM system, and obtain smoothing localization results. The proposed method analyzes the joint error distribution of the GNSS/visual SLAM system, uses the visual frame to invert the relative error offset of the GNSS from the dimensions of time and localization, performs error analysis and mutual verification based on the verification threshold. According to the mutual verification results, the GNSS spoofing is identified, and the corresponding back-end optimization strategy is selected to obtain a smoothing localization result. Through simulation, the time verification threshold and localization verification threshold of the proposed method are obtained under the condition that the sensors frequency and accuracy are set. The KITTI datasets in rural and urban scenes are used for verification. The simulation results show that our method can identify GNSS spoofing and provide credible and smoothing localization results in the case of GNSS spoofing occurs.

翻译:
提出了一种适用于全球导航卫星系统（GNSS）和视觉同步定位与测绘（SLAM）系统的平滑定位方法，以识别GNSS欺骗，优化GNSS/视觉SLAM系统的累积误差，并获得平滑定位结果。该方法分析了GNSS/视觉SLAM系统的联合误差分布，利用视觉框架从时间和定位维度反演GNSS的相对误差偏移，基于验证阈值进行误差分析和相互验证。根据相互验证结果，识别GNSS欺骗，并选择相应的后端优化策略，得到平滑定位结果。通过仿真，在设定传感器频率和精度的条件下，得到了该方法的时间验证阈值和定位验证阈值。使用农村和城市场景中的KITTI数据集进行验证。仿真结果表明，我们的方法能够识别GNSS欺骗，并在发生GNSS欺骗的情况下提供可靠、平滑的定位结果。

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