ASC-Net UAV BeiDou Navigation Spoofing

This dataset accompanies the research study and provides structured telemetry and simulation data used for evaluating real-time GNSS spoofing detection and mitigation in decentralized UAV swarms. The dataset includes multi-modal features such as BeiDou signal measurements (pseudorange, Doppler, C/N₀), IMU readings, inter-UAV communication metrics, Kalman filter innovations, and swarm-level consensus indicators. It captures diverse spoofing scenarios, including drag-off, meaconing, and multi-transmitter attacks, under both emulated and controlled experimental conditions. This resource supports reproducibility, benchmarking, and further research on resilient swarm navigation, distributed anomaly detection, and AI-driven cybersecurity for autonomous aerial systems.