Adversarial Attack on Radar-based Environment Perception Systems

Understand

Due to their robustness to degraded capturing conditions, radars are widely used for environment perception, which is a critical task in applications like autonomous vehicles.

• More specifically, Ultra-Wide Band (UWB) radars are particularly efficient for short range settings as they carry rich information on the environment.
• Recent UWB-based systems rely on Machine Learning (ML) to exploit the rich signature of these sensors.
• However, ML classifiers are susceptible to adversarial examples, which are created from raw data to fool the classifier such that it assigns the input to the wrong class.