The disruptive drone activity at airports requires an early warning system and Aveillant make a radar system that can do the job. The main problem is telling the difference between birds and drones where there may be one or two drones and 10s or 100s of birds. There is plenty of data including time series for how the targets move and the aim is to improve the discrimination capability of tracker using machine learning.
Specifically, the challenge is to understand whether there can be sufficient separability between birds and drones based on different features, such as flight profiles, length of the track, their states, and their dominance/correlation in the overall discrimination. Along with conventional machine learning techniques, the challenge is to consider how different techniques, such as deep neural networks, may perform in the discrimination task.