Rotor UAV’s Micro-Doppler Signal Detection and Parameter Estimation Based on FRFT-FSST

The micro-Doppler signal generated by the rotors of an Unmanned Aerial Vehicle (UAV) contains the structural features and motion information of the target, which can be used for detection and classification of the target, however, the standard STFT has the problems such as the lower time-frequency r...

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Auteurs principaux:	Huiling Hou, Zhiliang Yang, Cunsuo Pang
Format:	article
Langue:	EN
Publié:	MDPI AG 2021
Sujets:	rotor UAV FRFT FSST parameter estimation Chemical technology TP1-1185
Accès en ligne:	https://doaj.org/article/de9a3fee5073452b9ad806200752a625
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spelling	oai:doaj.org-article:de9a3fee5073452b9ad806200752a6252021-11-11T19:15:55ZRotor UAV’s Micro-Doppler Signal Detection and Parameter Estimation Based on FRFT-FSST10.3390/s212173141424-8220https://doaj.org/article/de9a3fee5073452b9ad806200752a6252021-11-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/21/7314https://doaj.org/toc/1424-8220The micro-Doppler signal generated by the rotors of an Unmanned Aerial Vehicle (UAV) contains the structural features and motion information of the target, which can be used for detection and classification of the target, however, the standard STFT has the problems such as the lower time-frequency resolution and larger error in rotor parameter estimation, an FRFT (Fractional Fourier Transform)-FSST (STFT based synchrosqueezing)-based method for micro-Doppler signal detection and parameter estimation is proposed in this paper. Firstly, the FRFT is used in the proposed method to eliminate the influence of the velocity and acceleration of the target on the time-frequency features of the echo signal from the rotors. Secondly, the higher time-frequency resolution of FSST is used to extract the time-frequency features of micro-Doppler signals. Moreover, the specific solution methodologies for the selection of window length in STFT and the estimation of rotor parameters are given in the proposed method. Finally, the effectiveness and accuracy of the proposed method for target detection and rotor parameter estimation are verified through simulation and measured data.Huiling HouZhiliang YangCunsuo PangMDPI AGarticlerotor UAVFRFTFSSTparameter estimationChemical technologyTP1-1185ENSensors, Vol 21, Iss 7314, p 7314 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	rotor UAV FRFT FSST parameter estimation Chemical technology TP1-1185
spellingShingle	rotor UAV FRFT FSST parameter estimation Chemical technology TP1-1185 Huiling Hou Zhiliang Yang Cunsuo Pang Rotor UAV’s Micro-Doppler Signal Detection and Parameter Estimation Based on FRFT-FSST
description	The micro-Doppler signal generated by the rotors of an Unmanned Aerial Vehicle (UAV) contains the structural features and motion information of the target, which can be used for detection and classification of the target, however, the standard STFT has the problems such as the lower time-frequency resolution and larger error in rotor parameter estimation, an FRFT (Fractional Fourier Transform)-FSST (STFT based synchrosqueezing)-based method for micro-Doppler signal detection and parameter estimation is proposed in this paper. Firstly, the FRFT is used in the proposed method to eliminate the influence of the velocity and acceleration of the target on the time-frequency features of the echo signal from the rotors. Secondly, the higher time-frequency resolution of FSST is used to extract the time-frequency features of micro-Doppler signals. Moreover, the specific solution methodologies for the selection of window length in STFT and the estimation of rotor parameters are given in the proposed method. Finally, the effectiveness and accuracy of the proposed method for target detection and rotor parameter estimation are verified through simulation and measured data.
format	article
author	Huiling Hou Zhiliang Yang Cunsuo Pang
author_facet	Huiling Hou Zhiliang Yang Cunsuo Pang
author_sort	Huiling Hou
title	Rotor UAV’s Micro-Doppler Signal Detection and Parameter Estimation Based on FRFT-FSST
title_short	Rotor UAV’s Micro-Doppler Signal Detection and Parameter Estimation Based on FRFT-FSST
title_full	Rotor UAV’s Micro-Doppler Signal Detection and Parameter Estimation Based on FRFT-FSST
title_fullStr	Rotor UAV’s Micro-Doppler Signal Detection and Parameter Estimation Based on FRFT-FSST
title_full_unstemmed	Rotor UAV’s Micro-Doppler Signal Detection and Parameter Estimation Based on FRFT-FSST
title_sort	rotor uav’s micro-doppler signal detection and parameter estimation based on frft-fsst
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/de9a3fee5073452b9ad806200752a625
work_keys_str_mv	AT huilinghou rotoruavsmicrodopplersignaldetectionandparameterestimationbasedonfrftfsst AT zhiliangyang rotoruavsmicrodopplersignaldetectionandparameterestimationbasedonfrftfsst AT cunsuopang rotoruavsmicrodopplersignaldetectionandparameterestimationbasedonfrftfsst
_version_	1718431615300927488

Rotor UAV’s Micro-Doppler Signal Detection and Parameter Estimation Based on FRFT-FSST

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