Abstract

Micro-Doppler (m-D) effect, induced by the rotation of rotor blades, introduces significant characteristics to identify small unmanned aerial vehicles (UAVs) in remote surveillance. As opposed to the Doppler signal induced by the translation, m-D signal is comparatively weak and consists of multiple frequency components. In this letter, we propose synchrosqueezing phase analysis (SPA) for the extraction of rotation signal with the multichannel radar. Based on the proposed signal model, this new method not only enables multivariate denoising and sharpening time-frequency (TF) representation, but also concentrates on the energy of rotation signal for the separation. Simulations are employed to demonstrate the validity of the proposed method in extracting the m-D features. Applications on field data further prove the potential in delineating m-D characteristics with higher precision and render that this technique is promising for the identification of small UAVs.

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