Decomposition of Multicomponent Micro-Doppler Signals Based on HHT-AMD

Micro-Doppler signals analysis has been emerging as an important topic in target identification, and relative research has been focusing on features extraction and separation of the radar signals. As a time-frequency representation, the Hilbert-Huang transform (HHT) could extract the accurate instan...

Full description

Bibliographic Details
Main Authors: Wenchao Li, Gangyao Kuang, Boli Xiong
Format: Article
Language:English
Published: MDPI AG 2018-10-01
Series:Applied Sciences
Subjects:
HHT
AMD
Online Access:http://www.mdpi.com/2076-3417/8/10/1801
id doaj-018709e0d1f04135b92607961a0e166d
record_format Article
spelling doaj-018709e0d1f04135b92607961a0e166d2020-11-24T21:46:26ZengMDPI AGApplied Sciences2076-34172018-10-01810180110.3390/app8101801app8101801Decomposition of Multicomponent Micro-Doppler Signals Based on HHT-AMDWenchao Li0Gangyao Kuang1Boli Xiong2State Key Laboratory of Complex Electromagnetic Environment Effects on Electronic and Information System, National University of Defense Technology, Changsha 410073, ChinaState Key Laboratory of Complex Electromagnetic Environment Effects on Electronic and Information System, National University of Defense Technology, Changsha 410073, ChinaState Key Laboratory of Complex Electromagnetic Environment Effects on Electronic and Information System, National University of Defense Technology, Changsha 410073, ChinaMicro-Doppler signals analysis has been emerging as an important topic in target identification, and relative research has been focusing on features extraction and separation of the radar signals. As a time-frequency representation, the Hilbert-Huang transform (HHT) could extract the accurate instantaneous micro-Doppler signature from the radar signals by empirical mode decomposition and Hilbert transform. However, HHT has the shortcoming that it cannot decompose the signals with close-frequency components. To solve this problem, an innovative decomposition method for multicomponent micro-Doppler signals based on Hilbert–Huang transform and analytical mode decomposition (HHT-AMD) is proposed. In this method, the multicomponent micro-Doppler signals are firstly decomposed by empirical mode decomposition, and the decomposed signal components are transformed by Hilbert transform to get the Hilbert-Huang spectrum and marginal spectrum. Through the spectrum processing, we get the frequency distribution of each signal component. The next step is to judge whether there exists frequency aliasing in each signal component. If there is aliasing, the AMD method is used to decompose the signal until all the decomposed signals are mono-component signals. Evaluation considerations are covered with numerical simulations and experiments on measured radar data. The results demonstrate that compared with conventional HHT, the proposed method yields accurate decomposition for multicomponent micro-Doppler signals and improves the robustness of decomposition. The method presented here can also be applied in various settings of non-stationary signal analysis and filtering.http://www.mdpi.com/2076-3417/8/10/1801micro-Dopplerfeature extractiontime-frequencyHHTAMDsignal decomposition
collection DOAJ
language English
format Article
sources DOAJ
author Wenchao Li
Gangyao Kuang
Boli Xiong
spellingShingle Wenchao Li
Gangyao Kuang
Boli Xiong
Decomposition of Multicomponent Micro-Doppler Signals Based on HHT-AMD
Applied Sciences
micro-Doppler
feature extraction
time-frequency
HHT
AMD
signal decomposition
author_facet Wenchao Li
Gangyao Kuang
Boli Xiong
author_sort Wenchao Li
title Decomposition of Multicomponent Micro-Doppler Signals Based on HHT-AMD
title_short Decomposition of Multicomponent Micro-Doppler Signals Based on HHT-AMD
title_full Decomposition of Multicomponent Micro-Doppler Signals Based on HHT-AMD
title_fullStr Decomposition of Multicomponent Micro-Doppler Signals Based on HHT-AMD
title_full_unstemmed Decomposition of Multicomponent Micro-Doppler Signals Based on HHT-AMD
title_sort decomposition of multicomponent micro-doppler signals based on hht-amd
publisher MDPI AG
series Applied Sciences
issn 2076-3417
publishDate 2018-10-01
description Micro-Doppler signals analysis has been emerging as an important topic in target identification, and relative research has been focusing on features extraction and separation of the radar signals. As a time-frequency representation, the Hilbert-Huang transform (HHT) could extract the accurate instantaneous micro-Doppler signature from the radar signals by empirical mode decomposition and Hilbert transform. However, HHT has the shortcoming that it cannot decompose the signals with close-frequency components. To solve this problem, an innovative decomposition method for multicomponent micro-Doppler signals based on Hilbert–Huang transform and analytical mode decomposition (HHT-AMD) is proposed. In this method, the multicomponent micro-Doppler signals are firstly decomposed by empirical mode decomposition, and the decomposed signal components are transformed by Hilbert transform to get the Hilbert-Huang spectrum and marginal spectrum. Through the spectrum processing, we get the frequency distribution of each signal component. The next step is to judge whether there exists frequency aliasing in each signal component. If there is aliasing, the AMD method is used to decompose the signal until all the decomposed signals are mono-component signals. Evaluation considerations are covered with numerical simulations and experiments on measured radar data. The results demonstrate that compared with conventional HHT, the proposed method yields accurate decomposition for multicomponent micro-Doppler signals and improves the robustness of decomposition. The method presented here can also be applied in various settings of non-stationary signal analysis and filtering.
topic micro-Doppler
feature extraction
time-frequency
HHT
AMD
signal decomposition
url http://www.mdpi.com/2076-3417/8/10/1801
work_keys_str_mv AT wenchaoli decompositionofmulticomponentmicrodopplersignalsbasedonhhtamd
AT gangyaokuang decompositionofmulticomponentmicrodopplersignalsbasedonhhtamd
AT bolixiong decompositionofmulticomponentmicrodopplersignalsbasedonhhtamd
_version_ 1725902213309530112