Research on Spectral Leakage Suppression Method of Coherent Wind Lidar Based on Hanning Self-Convolutional Window

Pulsed Coherent Doppler Wind Lidar (CDWL) usually utilizes a fixed-length range gate to divide the time domain of the echo signal, which can lead to the incomplete sampling of echo signals, resulting in a spectral leakage phenomenon and affecting the wind speed inversion accuracy. In this paper, we propose to utilize the Hanning Self-Convolutional Window (HSCW) to preprocess the wind speed echo signal, suppress the spectral leakage phenomenon, and improve the wind speed inversion accuracy of the algorithm. Simulation experiments show that the signal-to-noise ratio (SNR) is 3.28 dB higher than that of the Rectangular Window (RW), and the average root mean square error (RMSE) values of the first- to third-order HSCW are 164.2 kHz, 116.7 kHz, and 101.9 kHz, respectively. The comparison of wind speed with a commercial CDWL shows that the RMSE of the second-order HSCW inversion result is 0.184 m/s, while the RW and first-order HSCW are 0.449 m/s and 0.266 m/s, respectively.

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Publication Details

Journal
Applied Sciences
Published
2025-04-24
DOI
https://doi.org/10.3390/app15094709
Primary Topic
Advanced Optical Sensing Technologies
Type
article
Field-Weighted Citation Impact
0.00

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article

Research on Spectral Leakage Suppression Method of Coherent Wind Lidar Based on Hanning Self-Convolutional Window

Naiyuan Liang, Zixiao He, Peng Lin, Xiaonan Yu et al.
Applied Sciences
Advanced Optical Sensing Technologies
article

Research on Spectral Leakage Suppression Method of Coherent Wind Lidar Based on Hanning Self-Convolutional Window

Naiyuan Liang, Zixiao He, Peng Lin, Xiaonan Yu, Shoufeng Tong, Chen Su
article en

Abstract

Pulsed Coherent Doppler Wind Lidar (CDWL) usually utilizes a fixed-length range gate to divide the time domain of the echo signal, which can lead to the incomplete sampling of echo signals, resulting in a spectral leakage phenomenon and affecting the wind speed inversion accuracy. In this paper, we propose to utilize the Hanning Self-Convolutional Window (HSCW) to preprocess the wind speed echo signal, suppress the spectral leakage phenomenon, and improve the wind speed inversion accuracy of the algorithm. Simulation experiments show that the signal-to-noise ratio (SNR) is 3.28 dB higher than that of the Rectangular Window (RW), and the average root mean square error (RMSE) values of the first- to third-order HSCW are 164.2 kHz, 116.7 kHz, and 101.9 kHz, respectively. The comparison of wind speed with a commercial CDWL shows that the RMSE of the second-order HSCW inversion result is 0.184 m/s, while the RW and first-order HSCW are 0.449 m/s and 0.266 m/s, respectively.

Applied SciencesVol. 15(9)
Changchun University of Science and Technology (CN)
Changchun University of Science and Technology
Openalex Percentile: Top 91%
Advanced Optical Sensing Technologies
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Research on Spectral Leakage Suppression Method of Coherent Wind Lidar Based on Hanning Self-Convolutional Window — Naiyuan Liang, Zixiao He, et al. · Applied Sciences (2025) | TGRS Research Map | TGRS