Micro-Doppler radar deception and camouflage of airborne targets

Abstract

Micro-Doppler signatures are ubiquitous in radar-based object recognition and classification, as they contain information about the internal structure of observed targets. While modern machine learning algorithms achieve unprecedented accuracy in target classification, they are susceptible to deceptive manipulation by introducing intelligent artificial modulation to the target’s backscattered echoes. Here, we present the required foundations for successful passive deception, demonstrating experimentally the ability to camouflage a drone as a helicopter in the eyes of the investigating radar while maintaining radio silence. The concept can be used, for example, to manufacture low-cost, lightweight, and low-power devices that can, as an illustrative example, make a flock of birds appear as a swarm of drones to radar-based remote sensing platforms. This concept is applicable for implementation by passive time-dependent metasurfaces.