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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-11-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/21/21/7314 |
| _version_ | 1797511744133791744 |
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| author | Huiling Hou Zhiliang Yang Cunsuo Pang |
| author_facet | Huiling Hou Zhiliang Yang Cunsuo Pang |
| author_sort | Huiling Hou |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-10T05:52:23Z |
| format | Article |
| id | doaj.art-de9a3fee5073452b9ad806200752a625 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T05:52:23Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-de9a3fee5073452b9ad806200752a6252023-11-22T21:39:47ZengMDPI AGSensors1424-82202021-11-012121731410.3390/s21217314Rotor UAV’s Micro-Doppler Signal Detection and Parameter Estimation Based on FRFT-FSSTHuiling Hou0Zhiliang Yang1Cunsuo Pang2National Key Laboratory for Electronic Measurement Technology, North University of China, Taiyuan 030051, ChinaNational Key Laboratory for Electronic Measurement Technology, North University of China, Taiyuan 030051, ChinaNational Key Laboratory for Electronic Measurement Technology, North University of China, Taiyuan 030051, ChinaThe 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.https://www.mdpi.com/1424-8220/21/21/7314rotor UAVFRFTFSSTparameter estimation |
| spellingShingle | Huiling Hou Zhiliang Yang Cunsuo Pang Rotor UAV’s Micro-Doppler Signal Detection and Parameter Estimation Based on FRFT-FSST Sensors rotor UAV FRFT FSST parameter estimation |
| title | 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_short | 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 |
| topic | rotor UAV FRFT FSST parameter estimation |
| url | https://www.mdpi.com/1424-8220/21/21/7314 |
| work_keys_str_mv | AT huilinghou rotoruavsmicrodopplersignaldetectionandparameterestimationbasedonfrftfsst AT zhiliangyang rotoruavsmicrodopplersignaldetectionandparameterestimationbasedonfrftfsst AT cunsuopang rotoruavsmicrodopplersignaldetectionandparameterestimationbasedonfrftfsst |