The NRC develops first Canadian statistical airspace models

In recent years, the use of remotely piloted aircraft systems (RPAS), also known as drones, has gained significant momentum. However, the integration of these systems into airspace that is shared with traditional aviation presents a major challenge. Both must be able to safely coexist.

A frontal view of a passenger airplane on a runway. Another airplane is taking off in the background.
The Canadian airspace models will allow for a safer integration of RPAS into Canadian airspace, such as the vicinities of big cities and also airports.

To tackle this challenge, experts from the National Research Council of Canada's (NRC) Aerospace Research Centre have partnered with Carleton University, Transport Canada and NAV Canada to develop the first Canadian statistical airspace models.

Inspired by US airspace models, the Canadian models will allow for a safer integration of RPAS into Canadian airspace. This would include the vicinities of big cities and airports.

The Canadian airspace models support Canadian regulators in assessing the collision risks of drones flying beyond the visual line-of-sight of the pilot of operator. The models allow users to simulate tracks of various types of aircraft to better understand their behaviour in Canadian skies.

Technical requirements

The models were developed using the MATLAB and Python programming languages. Users must download the MATLAB programming platform to use them.

How to access

The models of light fixed-wing, medium fixed-wing and heavy fixed-wing aircraft, as well as the helicopter model, are now available on the NRC's GitHub collaboration platform.

Language

The documentation for the code is provided in English.

Access

Download the models from GitHub

Contact us

For more information on the Canadian airspace models, contact Iryna Borshchova, Research Officer, Aerospace Research Centre, at Iryna.Borshchova@nrc-cnrc.gc.ca.