@inproceedings{ba03a2c4ea844eaca62b0ccaff3d2368,
title = "The Micro-Doppler Features Extraction of Experimental Data of Chaff Cloud Scatter Dispersion Based on Empirical Mode Decomposition",
abstract = "This article studies the micro- Doppler characteristics of chaff cloud scatter based on the chaff filaments dispersion experiments. This paper highlights the extraction method of micro-Doppler features using the Empirical Mode Decomposition method incorporated with time-frequency analysis method. In order to extract the characteristics, the scattering signal is decomposed into a set of intrinsic-mode functions that are represented at different scales. The components are then reconstructed and analyzed by adopting the Short-Time Fourier Transform. After the separation of the Doppler frequency of the unexpanded chaff cluster radar return, the micro-Doppler frequency and micro- motion parameters of chaff filaments are estimated. The results of the experiment show that this extraction method has been successfully adopted to obtain the micro- Doppler features of chaff filaments. And a conclusion has been proved that the period of micro-Doppler frequency is determined by the period of chaff filaments vibration.",
keywords = "Empirical Mode Decomposition (EMD), chaff cloud, micro-Doppler, time-frequency analysis",
author = "Ran Li and Xinhong Hao and Song Bai and Ping Li",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019 ; Conference date: 11-12-2019 Through 13-12-2019",
year = "2019",
month = dec,
doi = "10.1109/ICSIDP47821.2019.9172904",
language = "English",
series = "ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019",
address = "United States",
}