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Updated: Apr 25, 2026

Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing

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Correlation-based LiDAR wind sensing using SiPM: methodology and indoor validation.

Guochao Li, Xiaonan Tao, Zhihao Liu

|April 24, 2026

Summary

This summary is machine-generated.

Silicon photomultiplier (SiPM) processing improves compact wind LiDAR systems. Pulse area estimation offers better wind speed accuracy than peak amplitude, enabling cost-effective, fixed-range wind retrieval.

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Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques

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Published on: March 12, 2019

Area of Science:

Atmospheric Science
Optical Engineering
Instrumentation

Background:

Wind LiDAR systems are crucial for atmospheric measurements.
Compact and cost-effective wind LiDARs are desirable for broader applications.
Silicon photomultipliers (SiPMs) offer potential for advanced LiDAR receiver technology.

Purpose of the Study:

To evaluate SiPM processing for cross-correlation wind LiDAR.
To compare two intensity estimators (peak amplitude vs. pulse area) for wind retrieval.
To assess the feasibility of compact, fixed-range SiPM-based wind LiDAR.

Main Methods:

Utilized a dual-beam, single-receiver architecture.
Employed a Monte Carlo SiPM response model for device-level analysis.
Conducted indoor fog-tunnel experiments for system-level wind retrieval evaluation.

Main Results:

Pulse area estimation yielded a lower mean relative retrieval error (8.75%) compared to peak amplitude (9.81%).
A larger fraction of operating points (74.18%) achieved below 10% relative error with pulse area estimation.
Demonstrated quantitative guidance for observable selection in SiPM-based correlation wind retrieval.

Conclusions:

SiPM processing, particularly pulse area estimation, enhances wind retrieval accuracy in correlation LiDAR.
The study supports the feasibility of compact, cost-effective, fixed-range wind LiDAR implementations using SiPMs.
Results provide valuable insights for designing future SiPM-based atmospheric measurement systems.