Ballistic Target Classification Using Machine Learning

Weapon locating radars are actively being used by militaries around the world, in order to protect a predetermined area from enemy fires. They achieve this by predicting the launch and impact points of ballistic targets which they detect. One of the most important steps in predicting the launch and impact points of an incoming ballistic target is to correctly identify the type of it. In this work, a ballistic target classifier with multiple decision steps using machine-learning methods is proposed and further research possibilities in this direction are discussed.