🚗🔐 Third contribution to ION GNSS+ 2025 published! – Greater security against GNSS spoofing and other threats. ➡️ Following our progress on AI-supported sensor fusion and edge-optimized LiDAR SLAM, we now present the third conference paper, which addresses another key component for secure, robust vehicle localization:

📌 Detection and Mitigation of Jamming, Meaconing, and Spoofing based on Machine Learning and Multi-Sensor Data

This paper shows how to not only detect GNSS interference—i.e., spoofing, jamming, and meaconing—but also mitigate it in a targeted manner by combining machine learning with additional sensor data such as IMU.

🔍 Highlights of the paper:
✔️ Deep learning for classification and detection of various GNSS interference events
✔️ Use of multiple features from GNSS measurements & inertial sensor technology
✔️ Robustness against false signals through targeted analysis of signal and sensor patterns
✔️ Multi-label approach for separate detection of jamming, spoofing, and meaconing
✔️ Direct application to autonomous navigation and assistance systems

These results show how AI methods can significantly improve the reliability of position determination in real-world scenarios.

📖 The first two papers (Multi-Sensor Fusion & Edge-LiDAR SLAM) can be found here:
👉 AI-supported sensor fusion – https://lnkd.in/dAQJaqbK

🔗 To the current paper: https://lnkd.in/dvjwX9Wt