AI 中文总结
本研究将全州CORS网络视为空间分布传感器，开发NCF和NCI框架，利用四星观测数据识别GNSS无意与蓄意干扰，为交通机构监测网络完整性提供方法。
AI 中文摘要
美国各州交通部（DOT）日益依赖全州连续运行参考站（CORS）网络，为智能交通系统提供基于全球导航卫星系统（GNSS）的高精度定位与授时服务。这些网络还能提供连续观测数据，支持区域GNSS完整性监测。本研究开发并验证了一种框架，将全州CORS网络视为空间分布传感器系统，用于在GNSS测量值偏离预期空间模式时，识别无意（环境）和蓄意（网络）干扰。我们开发了基于图的网络一致性框架（NCF），通过四个指标评估每个测站与其空间邻域的一致性：邻域残差、空间梯度、残差和图平滑度，将这些指标组合为网络一致性指数（NCI）。该框架使用阿拉巴马州交通部维护的CORS网络中50个测站两天的四星观测数据进行验证，采用垂直总电子含量变化（ΔVTEC）和TEC变化率指数（ROTI）作为空间相干观测值。该框架量化了全网空间一致性并识别了局部异常，检测到的异常表明相关测站的观测值偏离周边区域网络，预示潜在完整性问题。确定异常是由接收机故障、局部干扰、欺骗（spoofing）或其他原因导致的，有待进一步研究。本研究将全州CORS网络定义为区域GNSS完整性观测站，并提出用于基于图的空间完整性监测的NCF和NCI，交通机构可利用现有CORS观测数据实施该框架，以监测网络完整性并识别局部异常。
英文摘要
State departments of transportation (DOTs) in the United States increasingly rely on statewide continuously operating reference station (CORS) networks to support high-precision Global Navigation Satellite System (GNSS)-based positioning and timing for intelligent transportation systems. These networks also provide continuous observations that can support regional GNSS integrity monitoring. This study develops and demonstrates a framework that treats a statewide CORS network as a spatially distributed sensor system for identifying unintentional (environmental) and intentional (cyber) interference when GNSS measurements deviate from expected spatial patterns. We develop a graph-based Network Consistency Framework (NCF) that evaluates each station against its spatial neighborhood using four metrics: neighborhood residual, spatial gradient, residual, and graph smoothness. These metrics are combined into a Network Consistency Index (NCI). The framework is demonstrated using two consecutive days of four-constellation observations from 50 stations in the Alabama DOT-maintained CORS network, using changes in vertical total electron content (ΔVTEC) and the Rate of TEC Index (ROTI) as spatially coherent observables. The framework quantified network-wide spatial consistency and identified localized anomalies. Detected anomalies indicate stations whose observations deviated from the surrounding regional network, signaling potential integrity issues. Determining whether anomalies result from receiver faults, localized interference, spoofing, or other causes requires further investigation. This study introduces statewide CORS networks as regional GNSS integrity observatories and presents the NCF and NCI for graph-based spatial integrity monitoring. Transportation agencies can implement the framework using existing CORS observations to monitor network integrity and identify localized anomalies.
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