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eess.SP updates on arXiv.org

ECG-biometrics-bench: A Unified Framework for Reproducible Benchmarking of ECG Biometrics Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning Towards Improving Speaker Distance Estimation through Generative Impulse Response Augmentation Federated Learning with Hypergradient-based Online Update of Aggregation Weights Soft Graph Diffusion Transformer for MIMO Detection SPLICE: Latent Diffusion over JEPA Embeddings for Conformal Time-Series Inpainting Sequential Inference for Gaussian Processes: A Signal Processing Perspective Statistical Channel Fingerprint Construction for Massive MIMO: A Unified Tensor Learning Framework Recent Advances in mm-Wave and Sub-THz/THz Oscillators for FutureG Technologies Cross-Subject Generalization for EEG Decoding: A Survey of Deep Learning Methods Super-resolution Multi-signal Direction-of-Arrival Estimation by Hankel-structured Sensing and Decomposition Hankel and Toeplitz Rank-1 Decomposition of Arbitrary Matrices with Applications to Signal Direction-of-Arrival Estimation Adaptive Transform Coding for Semantic Compression EdgeSpike: Spiking Neural Networks for Low-Power Autonomous Sensing in Edge IoT Architectures Sparse Graph Learning from Sparse Data via Fiedler Number Maximization A Deep Learning Model for Battery State Prediction towards Intelligent Energy Management Transfer Learning for Tonal Noise Prediction in VRF Units Using Thermodynamic and Vibration Signals EVT-Based Generative AI for Tail-Aware Channel Estimation Monitoring exposure-length variations in submarine power cables using distributed fiber-optic sensing BandRouteNet: An Adaptive Band Routing Neural Network for EEG Artifact Removal Phase-Separated Complex Hilbert PCA on Markerless 3D Pose Estimation Data: A Global Phase Network and Its Extension to a Continuous Field on the Body Surface Selective Correlation Based Knowledge Distillation for Ground Reaction Force Estimation Deep Learning-Enabled Dissolved Oxygen Sensing in Biofouling Environments for Ocean Monitoring Speech Enhancement Based on Drifting Models Robust and Clinically Reliable EEG Biomarkers: A Cross Population Framework for Generalizable Parkinson's Disease Detection An AI-Based Supervisory Measurement Integrity Validation Layer for Cyber-Resilient AC/DC Protection in Inverter-Based Microgrids Explainable AI in Speaker Recognition -- Making Latent Representations Understandable Time-Localized Parametric Decomposition of Respiratory Airflow for Sub-Breath Analysis NAKUL-Med: Spectral-Graph State Space Models with Dynamics Kernels for Medical Signals An Algorithm for On-Sensor Agnostic Detection of Changes in Human Activity for Ultra-Low-Power Applications
UnReference: analysis of the effect of spoofing on RTK re...
Marco Spanghero, Panos Papadimitratos · 2025-03-26 · via eess.SP updates on arXiv.org

Global Navigation Satellite Systems (GNSS) provide standalone precise navigation for a wide gamut of applications. Nevertheless, applications or systems such as unmanned vehicles (aerial or ground vehicles and surface vessels) generally require a much higher level of accuracy than those provided by standalone receivers. The most effective and economical way of achieving centimeter-level accuracy is to rely on corrections provided by fixed \emph{reference station} receivers to improve the satellite ranging measurements. Differential GNSS (DGNSS) and Real Time Kinematics (RTK) provide centimeter-level accuracy by distributing online correction streams to connected nearby mobile receivers typically termed \emph{rovers}. However, due to their static nature, reference stations are prime targets for GNSS attacks, both simplistic jamming and advanced spoofing, with different levels of adversarial control and complexity. Jamming the reference station would deny corrections and thus accuracy to the rovers. Spoofing the reference station would force it to distribute misleading corrections. As a result, all connected rovers using those corrections will be equally influenced by the adversary independently of their actual trajectory. We evaluate a battery of tests generated with an RF simulator to test the robustness of a common DGNSS/RTK processing library and receivers. We test both jamming and synchronized spoofing to demonstrate that adversarial action on the rover using reference spoofing is both effective and convenient from an adversarial perspective. Additionally, we discuss possible strategies based on existing countermeasures (self-validation of the PNT solution and monitoring of own clock drift) that the rover and the reference station can adopt to avoid using or distributing bogus corrections.