Treating Statewide CORS Networks as Spatially Distributed Sensors for GNSS Integrity Monitoring under Unintentional and Deliberate Threats

2026-08-09

AI Summary

This study addresses the challenge of integrity monitoring for GNSS under both unintentional disturbances—such as ionospheric scintillation—and intentional threats like spoofing. It proposes, for the first time, leveraging statewide Continuously Operating Reference Station (CORS) networks as spatially distributed sensor systems to develop a graph-based Network Consistency Framework (NCF) and a corresponding Network Consistency Index (NCI). By integrating multidimensional indicators—including spatial neighborhood analysis, differential vertical total electron content (ΔVTEC), and rate of TEC index (ROTI)—the approach enables regional-scale spatial anomaly detection. Validation using quad-constellation GNSS data from 50 CORS stations across Alabama demonstrates that the method effectively quantifies spatial consistency across the network and accurately identifies local anomalous stations that deviate from regional patterns.

Abstract

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.

Problem

• GNSS integrity monitoring
• CORS network
• spatial anomaly detection
• unintentional interference
• deliberate threats

Innovation

• Network Consistency Framework
• spatial integrity monitoring
• CORS network
• GNSS spoofing detection
• graph-based anomaly detection