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NADODE - Drone Navigation with GNSS Interference Monitoring in GNSS Denied Environment

|   Call 2021

Identification of optimal non-GNSS navigation sensors and/or sensor fusion approaches. Realization of more sensitive interference detection algorithms (Karhunen-Loève- Transformation - KLT). Proof-of-concept by flying a drone with a demonstrator for non-

GNSS navigation and KLT detection at the Seetaler Alpe.

Increasing threats to Global Navigation Satellite Systems (GNSS) from intentional interference (interference, jamming, spoofing) require, on the one hand, consideration of (multiple) sensors or sensor fusions which can replace GNSS, especially for safety-critical and military applications, and, on the other hand, the development of new methods for higher sensitivity to detect and localize the interferers from the air (UAVs, drones) to determine near real-time times of impaired or impossible GNSS navigation. It is therefore particularly worth mentioning the case when drones have to fly with alternative navigation due to impaired GNSS navigation in order to detect and eliminate the interference from the ground as well as from the air (from drones).

The project thus contributes to point 4.1.3 Robotics - Unmanned systems and protection against UAV threats, and in detail to "Multi-sensor fusion for the navigation of autonomous systems and swarms of autonomous systems in GNSS denied environments” of the FORTE program.

The first project goal is the identification of optimal non-GNSS navigation sensors and/or sensor fusion approaches for civil and military applications. This is done through extensive simulations, criteria matrices to be developed depending on the specific application and SWOT analyses as well as considering existing field reports in the literature.

The second goal is the realization of more sensitive interference detection algorithms, specifically the Karhunen-Loève transformation (KLT) in software, which is tested by simulation with regard to various GNSS interferences and compared with the methods used so far, e.g., the Fast Fourier Transform (FFT). Finally, it should be tested in practice with goal (3).

The third goal is by combinig the goals (1) and (2): Proof-of-Concept by flying a drone with a demonstrator for a real non-GNSS navigation and KLT detection for the first time at the Seetaler Alpe military training area (TÜPL). The LOKI signal generator developed by IGASPIN is used as the jammer and spoofer.

Another goal is the application of a specific method for non-GNSS navigation. For this purpose, image-based localization using passive sensors is selected and used. The basic principle of visual navigation is the comparison of image information to an existing (or simultaneously created) visual representation of the environment. This non-GNSS navigation variant is to be evaluated using recorded data. It is done in post-processing with real recorded data.

The solution approaches also contribute to goal 9 of the SDGs, "Resilient infrastructure and sustainable industrialization", by developing a way of eliminating interference from GNSS signals, which are used for many applications in everyday life (navigation, communication, road traffic, air traffic, banks, etc.) in a timely and highly mobile manner. The project thus contributes to improving the security and availability of critical infrastructure and services based on it.

[Translate to English:] Bundesministerium für Finanzen
[Translate to English:] Österreichische Forschungsförderungsgesellschaft - FFG
[Translate to English:] Bundesministerium für Landesverteidigung