BorderUAS Semi-autonomous border surveillance platform combining next generation unmanned aerial vehicles with ultra-high-resolution multi-sensor surveillance payload

Summary

The project will combine for the first time a multi-role lighter-than-air (LTA) unmanned aerial vehicle (UAV) with an ultra-high resolution multi-sensor surveillance payload supporting border surveillance as well as search & rescue applications, and specifically rough terrain detection. The sensor payload will include synthetic aperture radar (SAR), laser detection and ranging (LADAR), shortwave/longwave infrared (SWIR/LWIR) and acoustic cameras for direct target detection, as well as optical and hyperspectral cameras for indirect detection (via vegetation disturbance).
The project will use the ground-based infrastructure of border police units (command & control centres), innovative data models (to identify illegal crossing patterns and preferred routes) and advanced audio/video analytics and storage (to
provide additional detection capabilities).
The technology concepts will be validated in the field by 6 border police units (Greece, Bulgaria, Romania, Moldova, Ukraine, Belarus) covering 3 major illegal migration routes into Europe (Eastern Mediterranean, Western Balkan and Eastern
Borders Routes), which represent 58% of all illegal border crossings detected and are also the most used for smuggling of drugs, weapons and stolen vehicles.
The combined solution will provide high coverage, resolution and revisit time with a lower cost (4 EUR/kg/hr) than satellites and higher endurance (100 kg payload for 12 hours) than drones. Based on the field trial results, the consortium expects to
develop a solution that can be deployed further by European border polices after project completion. The project will also involve the contribution of NGOs working with illegal migration and human right protection issues, as well as regulatory
experts dealing with the ethics and privacy requirements of border surveillance solutions

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More information & hyperlinks

Web resources:	https://cordis.europa.eu/project/id/883272
Start date:	01-06-2020
End date:	31-05-2024
Total budget - Public funding:	6 997 332,00 Euro - 6 997 332,00 Euro

Cordis data

Original description

The project will combine for the first time a multi-role lighter-than-air (LTA) unmanned aerial vehicle (UAV) with an ultra-high
resolution multi-sensor surveillance payload supporting border surveillance as well as search & rescue applications, and
specifically rough terrain detection. The sensor payload will include synthetic aperture radar (SAR), laser detection and
ranging (LADAR), shortwave/longwave infrared (SWIR/LWIR) and acoustic cameras for direct target detection, as well as
optical and hyperspectral cameras for indirect detection (via vegetation disturbance).
The project will use the ground-based infrastructure of border police units (command & control centres), innovative data
models (to identify illegal crossing patterns and preferred routes) and advanced audio/video analytics and storage (to
provide additional detection capabilities).
The technology concepts will be validated in the field by 6 border police units (Greece, Bulgaria, Romania, Moldova,
Ukraine, Belarus) covering 3 major illegal migration routes into Europe (Eastern Mediterranean, Western Balkan and Eastern
Borders Routes), which represent 58% of all illegal border crossings detected and are also the most used for smuggling of
drugs, weapons and stolen vehicles.
The combined solution will provide high coverage, resolution and revisit time with a lower cost (4 EUR/kg/hr) than satellites
and higher endurance (100 kg payload for 12 hours) than drones. Based on the field trial results, the consortium expects to
develop a solution that can be deployed further by European border polices after project completion. The project will also
involve the contribution of NGOs working with illegal migration and human right protection issues, as well as regulatory
experts dealing with the ethics and privacy requirements of border surveillance solutions