The DLR Artificial Intelligence Navigation Challenge for resilience and autonomy was looking for solutions that enable automation and autonomy with reliable PNT – positioning, navigation, and timing – and strengthen PNT with smart approaches while providing maximum benefit to the user community.
Those are the TOP 3 submissions to the DLR Artificial Intelligence Navigation Challenge. Congratulations to the winning solution!
Signal-In-Space Analysis Using AI
A Secure GNSS Receiver Powered by Embedded AI
Since public GNSS signals cannot be authenticated, they can be imitated. This is known as a spoofing attack. It poses a threat to users because their navigation systems could receive fake and misleading signals that can cause a route deviation.
Automated and autonomous systems are especially vulnerable. Humans and valuable assets are exposed to this threat. Smartphones and vehicles use GNSS for navigation and are operated by humans, which is why they are perfect targets for those seeking to cause people harm.
Apart from diverting a car from its route, think of a mobile phone being spoofed: Instead of following legitimate GNSS signals, the owner could be redirected to a dangerous place by fake positioning signals from an attacker.
This project aims to develop a secure GNSS receiver. The device is designed for worldwide civilian use and for users with high security requirements which are not covered by any secure GNSS variant.
The receiver will detect and correct route deviations by verifying the legitimacy of the GNSS signals. An artificial intelligence engine will determine the authenticity of signals and reject any others. Further security mechanisms will ensure the integrity and data privacy of the device’s components.
Submitted by Sadiel de la Fe Siverio
*A mutual agreement between the winner and DLR about the focus of work is required.
The prize itself is a bundle of activities that are executed purely within DLR. There is no way to convert this into a cash prize to be paid to the winner or other external parties. While all contestants will demonstrate their innovation competence merely by participating, the winner will enjoy the added benefit of having the Galileo Masters DLR Special Prize 2019 on their record as a testament of quality.
Submissions to DLR Artificial Intelligence Navigation Challenge for resilience and autonomy will be assessed against the following criteria:
Benefit to the user community
Ideas and innovations will contribute to further optimising the operation and the evolution by honing existing approaches as well as with completely new thoughts to refuel the ideas tank
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German Aerospace Center (DLR)
Robert Klarner
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