Method and device for generating learning data for an artificial intelligence machine for aircraft landing assistance

A computer-implemented method for generating labeled training data able to be used by an artificial intelligence machine implementing a deep learning image processing algorithm, the method comprising at least the steps of:

• defining parameters for a scenario of an aircraft approaching a runway;
• using the parameters of the scenario in a flight simulator to generate simulated flight data, said flight simulator being configured so as to simulate said aircraft in the approach phase and an associated autopilot;
• using the simulated flight data in a sensor simulator to generate simulated sensor data, said sensor simulator being configured so as to simulate a forward-facing sensor on board an aircraft and able to provide sensor data representative of information of interest of a runway, said simulated sensor data that are generated being representative of information of interest of said runway;
• using the simulated flight data and the simulated sensor data to generate a ground truth, said ground truth associated with the simulated sensor data forming a pair of simulated labeled training data;
• and
• wherein the step of generating the ground truth consists in:
• generating a first-level ground truth comprising labeling data representative of characteristics of the simulated runway, without a visibility restriction;
• detecting the visibility limit by identifying areas without visibility in the simulated sensor data;
• and
• correcting the first-level ground truth with the identified areas without visibility in order to generate said ground truth.