NLR researches drone DAA system based on miniaturised transponder signal technology

The Dutch aerospace research agency NLR is working on developing a Detect And Avoid (DAA) system based on a Cooperative Traffic Sensor using transponder signal technology.

Within the Airborne Data Collection on Resilient System Architectures (ADACORSA) project, such a sensor will be developed and tested in cooperation with the partners, says the research agency.

According to the agency’s website the main challenges of the project are:

  • The form factor and power requirements of current DAA systems are not suitable for small and mid-sized unmanned aircraft.
  • Due to frequency saturation of the manned aircraft transponder frequencies, drones cannot be equipped with ADS-B transponders.
  • Manned aircraft with both Mode-S and ADS-B transponders need to be detected.

The solution

  • Miniaturisation of the DAA system suitable to be integrated onboard of small and mid-sized unmanned aircraft.
  • Sensor suite advancement to include a direction finder to measure the azimuth such that the relative position to the intruders is known
  • Information from ADS-B (manned intruder aircraft) will be used to further increase detection of current airspace users

NLR’s Direction Finder for the Cooperative Traffic Sensor (CTS) will be integrated with a Mode-S interrogator, developed by project partner Celestia Technology Group. “The DAA system uses algorithms developed by NLR for semi-automatic avoidance of other aircraft. These algorithms feature both Remain Well Clear (RWC) and Collision Avoidance (CA) functionalities. The RWC functionality takes into account the rules-of-the-air to calculate a new route for the unmanned aircraft. The calculation is performed onboard to be independent of a data link and allows a fully autonomous system in the future. The DAA system will be integrated and flight tested in the DAA Flying Testbed at the NLR Drone Flight Test Centre. Finally, the developed system will be demonstrated in a logistic support use case.”

For more information

https://www.nlr.org/case/case-detect-and-avoid-system-adacorsa/

(Image: Shutterstock)

Share this:
D-Fend advert. Click for website