In-Flight Tests of Intruder Detection Vision System

Area of Science:

• Aerospace Engineering
• Computer Vision
• Avionics Systems

Background:

• Increasing integration of manned and unmanned aerial vehicles (UAVs) in shared airspace presents new safety challenges.
• Light aircraft, ultralight aircraft, and UAVs require advanced collision avoidance systems.
• The IDAAS project aims to address these challenges with innovative detection and avoidance technologies.

Purpose of the Study:

• To present research and practical tests of the intruder detection vision system developed within the IDAAS project.
• To discuss the formal requirements for aircraft anti-collision systems.
• To detail the IDAAS system concept and its image processing algorithms.

Main Methods:

• Development of a vision-based intruder detection system (IDAAS).
• Implementation of image processing algorithms for threat identification.
• Conducting dedicated flight tests using an ultralight aircraft.

Main Results:

• Initial flight tests indicate the feasibility of using vision methods for intruder detection.
• The system demonstrated potential for effective detection in various airspace scenarios.
• Certain environmental conditions were identified as potentially hindering detection performance.

Conclusions:

• The IDAAS vision system shows promise for enhancing airspace safety for light and unmanned aerial vehicles.
• Further research is needed to address limitations and improve detection reliability under difficult conditions.
• The system contributes to the development of advanced collision avoidance solutions for the evolving aviation landscape.