Abstract
Secondary motions of a target, such as rotating blades of a helicopter's main rotor, induce a Doppler modulation around the main Doppler shift. This represents a unique feature of the target itself, known as micro-Doppler signature, and can be used for classification purposes. In this student research highlight a model-based automatic helicopter classification algorithm is presented. It is a parametric classification approach based on a sparse signal recovery method and it is independent of both the initial position of the blades and the aspect angle. The algorithm is tested on simulated and real data.
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