Detect and Avoid System for RPAS

Unmanned Aircraft Systems (UAS), and more specifically Remotely Piloted Aircraft Systems (RPAS), are increasingly becoming a part of our day to day lives. The commercial use of these vehicles has some challenges which lie in integrating the worlds of manned and unmanned aircraft in a safe and efficient way, as both types of aircraft will use the same airspace.


The absence of a pilot on-board brings the challenge of matching the ability of the RPAS to Detect and Avoid (DAA) other traffic, managing dangerous situations, like potential collisions with other airspace users, clouds and severe weather conditions, obstacles and ground operations at airports.

Many of the smaller RPAS operate at altitudes below 500ft AGL. According to ICAO Annex 2 this is the lowest available VFR altitude, and thus creates a possible boundary between smaller RPAS and manned aircraft. However, nearly every State allows manned operations below this altitude and coexisting with small undetectable RPAS poses a safety challenge. For now, no restrictions have been put in place regarding the maximum number of small RPAS allowed to operate in a certain area.

Integration of RPAS into the airspace between 500ft and 60,000ft as either IFR or VFR is challenging due to the fact that RPAS will have to fit into the ATM environment and adapt accordingly. Many RPAS aspects such as latency and detect and avoid have never been before addressed within this environment for manned aviation, simply because of the fact that a pilot is on-board the aircraft, capable of handling these issues in a safe and timely manner. Also, these human capabilities have never been translated into system performance as they were placed under “good airmanship” for see and avoid, or simply not addressed at all.

OE is developing basic tools and techniques required for a DAA system. In particularr, we have focused on:

  • Translating and quantifying the safety attributes of manned aircraft (See and Avoid) for unmanned vehicles
  • Modelling different detection techniques such as Mini-Radar, LiDAR, SLAM, image processing, and sonar
  • Developing appropriate avoidance algorithms and re-planning techniques
This R&D project involves basic modeling and simulations of the air traffic and the interaction between the RPAS (equipped with a DAA system) and its surrounding air traffic.