Research on optimizing the optical local-oscillator power of Coherent Doppler LiDAR to enhance wind velocity measurements

Abstract Due to weak echo signals that become progressively overwhelmed by noise, measurement accuracy and effective detection range of the Coherent Doppler wind LiDAR (CDL) are often compromised. While increasing the optical local-oscillator power (OLP) can amplify the echo signal, it is constrained by the nonlinear effects of the detector. This paper introduces a method for optimizing the OLP in CDL systems. Theoretical analysis has been proposed to explore the amplification effect of OLP on echo signals, and the nonlinear effects of detectors have been studied. Simulations are performed to explore the influence of varying OLP on the signal-to-noise ratio (SNR) across different detector α (quadratic nonlinear coefficient) values. The spectral analysis method is used to directly compute the SNR of actual atmospheric wind field signals under various OLP settings. Results demonstrate consistency between calculated and simulated values, enabling determination of optimal OLP and the detector α values from fitted curves. Comparative experiments confirm significant enhancement in effective detection range (> 1.5 km) with ± 0.5 m/s accuracy. The innovation of this study lies in combining the OLP optimization method with real atmospheric wind field echo signal experiments. It addresses the challenges of directly measuring the nonlinear parameters of the detector and determining the optimal OLP. This study offers valuable theoretical and experimental insights for enhancing the wind measurement performance of CDL.

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Publication Details

Journal
Journal of Instrumentation
Published
2024-10-01
DOI
https://doi.org/10.1088/1748-0221/19/10/p10028
Citations
3
Primary Topic
Wind Energy Research and Development
Type
article
Field-Weighted Citation Impact
3.90
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article

Research on optimizing the optical local-oscillator power of Coherent Doppler LiDAR to enhance wind velocity measurements

Bangxin Wang, Chenbo Xie, Hui Zhou, Yalin Hu et al.
3 citations
Journal of Instrumentation
Wind Energy Research and Development
3.90
article

Research on optimizing the optical local-oscillator power of Coherent Doppler LiDAR to enhance wind velocity measurements

Bangxin Wang, Chenbo Xie, Hui Zhou, Yalin Hu, Yingjian Wang, Kunming Xing
article en
3 citations

Abstract

Abstract Due to weak echo signals that become progressively overwhelmed by noise, measurement accuracy and effective detection range of the Coherent Doppler wind LiDAR (CDL) are often compromised. While increasing the optical local-oscillator power (OLP) can amplify the echo signal, it is constrained by the nonlinear effects of the detector. This paper introduces a method for optimizing the OLP in CDL systems. Theoretical analysis has been proposed to explore the amplification effect of OLP on echo signals, and the nonlinear effects of detectors have been studied. Simulations are performed to explore the influence of varying OLP on the signal-to-noise ratio (SNR) across different detector α (quadratic nonlinear coefficient) values. The spectral analysis method is used to directly compute the SNR of actual atmospheric wind field signals under various OLP settings. Results demonstrate consistency between calculated and simulated values, enabling determination of optimal OLP and the detector α values from fitted curves. Comparative experiments confirm significant enhancement in effective detection range (> 1.5 km) with ± 0.5 m/s accuracy. The innovation of this study lies in combining the OLP optimization method with real atmospheric wind field echo signal experiments. It addresses the challenges of directly measuring the nonlinear parameters of the detector and determining the optimal OLP. This study offers valuable theoretical and experimental insights for enhancing the wind measurement performance of CDL.

Journal of InstrumentationVol. 19(10)
University of Science and Technology of China (CN), Chinese Academy of Sciences (CN), Anhui Institute of Optics and Fine Mechanics (CN)
Openalex Percentile: Top 6%
Wind Energy Research and Development
3.90
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