Open AccessIntrinsic synchrosqueezing analysis on micro‐Doppler features for small unmanned aerial vehicles identification with dual‐channel radar
Author(s) -
Zhao Yichao,
Su Yi
Publication year - 2021
Publication title -
iet microwaves, antennas and propagation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.555
H-Index - 69
eISSN - 1751-8733
pISSN - 1751-8725
DOI - 10.1049/mia2.12087
Subject(s) - signal (programming language) , hilbert–huang transform , doppler effect , computer science , radar , signal processing , channel (broadcasting) , instantaneous phase , noise (video) , artificial intelligence , rotor (electric) , remote sensing , computer vision , physics , geology , filter (signal processing) , telecommunications , quantum mechanics , astronomy , image (mathematics) , programming language
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 data‐association 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 noise‐assisted 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.