Intrinsic synchrosqueezing analysis on micro‐Doppler features for small unmanned aerial vehicles identification with dual‐channel radar

Abstract

The micro-Doppler (m-D) effect depends on the rotation of rotor blades in addition to the translation of the platform. Thus it is a characteristic for identifying small unmanned aerial vehicles (UAVs). However, compared with the Doppler signal induced by the translation of the platform, the m-D signal is weak. In this article, a highly localised dataassociation method, intrinsic synchrosqueezing analysis (ISA), is proposed for estimating m-D characteristics from the returned signal of small UAVs with a dual-channel radar. Employing synchrosqueezing transform on intrinsic mode functions derived from noiseassisted multivariate empirical mode decomposition, the proposed ISA method separates the Doppler signal and enables denoising and sharpening time-frequency representation of the m-D signal. Simulation results confirm the theoretical analysis, showing the feasibility of estimating m-D features in a noisy environment. Applications on field data illustrate brighter prospects for identifying small UAVs.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

A method for transforming 2D imaging features with the AFSS‐loaded rotating Luneberg lens reflector

“…Synthetic aperture radar (SAR) can form two-dimensional (2D) imaging results of the desired target area with all-day, allweather, and high-resolution imaging capability [1][2][3]. The micro-motion target can modulate the non-stationary phase on the SAR echo signal due to micro-Doppler characteristics [4][5][6][7]. The defocus effect of the target imaging feature for SAR is discovered along the azimuth direction, which has received intensive attentions in the field of anti-recognition [8][9][10][11][12].…”