AAV Parameters Estimation Based on Improved Time-Frequency Ridge Extraction and Hough Transform
The micro-Doppler effect caused by the rotation of autonomous aerial vehicle (AAV) rotors plays a crucial role in AAV detection and identification, as it can reflect the micro-movement characteristics of the target, enabling the estimation of the blade length and rotation speed. However, existing me...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/11091279/ |
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| author | Yongji Yu Yonghong Ruan Junjie Zhong |
| author_facet | Yongji Yu Yonghong Ruan Junjie Zhong |
| author_sort | Yongji Yu |
| collection | DOAJ |
| description | The micro-Doppler effect caused by the rotation of autonomous aerial vehicle (AAV) rotors plays a crucial role in AAV detection and identification, as it can reflect the micro-movement characteristics of the target, enabling the estimation of the blade length and rotation speed. However, existing methods are prone to noise interference and exhibit poor performance in extracting multi-rotor and multi-component signals. In this paper, we first construct a AAV rotor echo model for frequency-modulated radar systems and derive the mapping relationship between rotor parameters and micro-Doppler characteristic components. First-Order short-time Fourier transform synchrosqueezed transform (FSST) is proposed for extracting micro-Doppler features. Specifically, a novel AAV parameter estimation method is investigated, which is based on an improved time-frequency ridge extraction and Hough transform, following a detailed analysis of the micro-Doppler time-frequency spectrum. Finally, the effectiveness of the method is validated through experimental data. Compared to traditional methods, this approach improves the accuracy of multi-rotor, multi micro-Doppler signal parameter estimation. |
| format | Article |
| id | doaj-art-684782a8d8d94635a45e7b9828256092 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-684782a8d8d94635a45e7b98282560922025-08-20T03:56:05ZengIEEEIEEE Access2169-35362025-01-011313107413108710.1109/ACCESS.2025.359178711091279AAV Parameters Estimation Based on Improved Time-Frequency Ridge Extraction and Hough TransformYongji Yu0Yonghong Ruan1https://orcid.org/0009-0007-9436-4495Junjie Zhong2Yunnan Vocational College of Mechanical and Electrical Technology, Kunming, Yunnan, ChinaSchool of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, ChinaSchool of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, ChinaThe micro-Doppler effect caused by the rotation of autonomous aerial vehicle (AAV) rotors plays a crucial role in AAV detection and identification, as it can reflect the micro-movement characteristics of the target, enabling the estimation of the blade length and rotation speed. However, existing methods are prone to noise interference and exhibit poor performance in extracting multi-rotor and multi-component signals. In this paper, we first construct a AAV rotor echo model for frequency-modulated radar systems and derive the mapping relationship between rotor parameters and micro-Doppler characteristic components. First-Order short-time Fourier transform synchrosqueezed transform (FSST) is proposed for extracting micro-Doppler features. Specifically, a novel AAV parameter estimation method is investigated, which is based on an improved time-frequency ridge extraction and Hough transform, following a detailed analysis of the micro-Doppler time-frequency spectrum. Finally, the effectiveness of the method is validated through experimental data. Compared to traditional methods, this approach improves the accuracy of multi-rotor, multi micro-Doppler signal parameter estimation.https://ieeexplore.ieee.org/document/11091279/Micro-Doppler feature extractionrotor autonomous aerial vehicle (AAV) parameter estimationtime-frequency analysistime-frequency ridgeHough transform |
| spellingShingle | Yongji Yu Yonghong Ruan Junjie Zhong AAV Parameters Estimation Based on Improved Time-Frequency Ridge Extraction and Hough Transform IEEE Access Micro-Doppler feature extraction rotor autonomous aerial vehicle (AAV) parameter estimation time-frequency analysis time-frequency ridge Hough transform |
| title | AAV Parameters Estimation Based on Improved Time-Frequency Ridge Extraction and Hough Transform |
| title_full | AAV Parameters Estimation Based on Improved Time-Frequency Ridge Extraction and Hough Transform |
| title_fullStr | AAV Parameters Estimation Based on Improved Time-Frequency Ridge Extraction and Hough Transform |
| title_full_unstemmed | AAV Parameters Estimation Based on Improved Time-Frequency Ridge Extraction and Hough Transform |
| title_short | AAV Parameters Estimation Based on Improved Time-Frequency Ridge Extraction and Hough Transform |
| title_sort | aav parameters estimation based on improved time frequency ridge extraction and hough transform |
| topic | Micro-Doppler feature extraction rotor autonomous aerial vehicle (AAV) parameter estimation time-frequency analysis time-frequency ridge Hough transform |
| url | https://ieeexplore.ieee.org/document/11091279/ |
| work_keys_str_mv | AT yongjiyu aavparametersestimationbasedonimprovedtimefrequencyridgeextractionandhoughtransform AT yonghongruan aavparametersestimationbasedonimprovedtimefrequencyridgeextractionandhoughtransform AT junjiezhong aavparametersestimationbasedonimprovedtimefrequencyridgeextractionandhoughtransform |