Locating GNSS interferences using Artificial Intelligence

PINPOINT National Risk Management for GSVP Missions using OSINT and PNT Monitoring

The primary objective is to develop a comprehensive risk analysis template with a strong focus on inclusivity and non-discrimination principles. This initiative is built upon an in-depth environmental analysis of at least two chosen CSDP missions. Our interdisciplinary approach places particular emphasis on gender and GSK considerations, encompassing ethical, socio-political, demographic, human rights, ecological, and technological facets, along with diversity and equality concerns. The resulting benefits include the formulation of a risk analysis template and actionable recommendations for PNT and OSINT-based strategies.

CSDP missions risk template and recommendations by PNT and OSINT-based strategies

To mitigate risks, we enhance open-source information with reliable PNT data in a preliminary design. We leverage NLP (Natural Language Processing) and complementary technologies to process multimedia content in various languages and media formats. This approach helps us develop indicators that portray the temporal and spatial aspects of potential threat scenarios and enhance the credibility of information. PNT monitoring is carried out using portable and intelligent sensors on both stationary and mobile platforms.

AI in GNSS technology

Artificial Intelligence is deployed to identify and locate GNSS interference, including jamming, meaconing, and spoofing attempts. Additionally, we employ image-based technology for automatic PNT availability detection. Our research extends to data collection, analysis, and fusion methods that bridge OSINT and PNT, aiming to reduce risks associated with factors such as weather/climate, electricity/water supply, population sentiment/crime rates, and disease/hygiene.

The establishment of an exploitation roadmap facilitates clarity among project partners regarding the continuation and commercial utilization of relevant research findings.

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