Signal simulation framework for assessing wind speed error of a Doppler wind lidar

Area of Science:

• Atmospheric physics
• Optical remote sensing
• Instrumentation and measurement

Background:

• Accurate wind speed measurement is crucial for coherent wind lidar calibration.
• Traditional calibration methods (flywheel, wind cups) have significant limitations in simulating realistic atmospheric conditions and require unpredictable wind.
• These limitations hinder precise calibration and validation of coherent wind lidar systems.

Purpose of the Study:

• To propose a new method for simulating atmospheric wind speed profiles and aerosol scenarios.
• To validate and optimize coherent wind lidar performance, including measurement accuracy, wind speed resolution, and retrieval algorithms.
• To investigate the influence of aerosol backscatter intensity on wind speed retrieval accuracy.

Main Methods:

• Simulating backscatter signal intensity using amplitude modulation (AM).
• Simulating wind speed variations with altitude using frequency modulation (FM).
• Analyzing the impact of carrier-to-noise ratio (CNR) on wind speed retrieval accuracy.

Main Results:

• The proposed simulation method effectively validates coherent wind lidar performance.
• Wind speed retrieval errors are minimized at an optimal CNR, which varies with wind speed.
• Achieved a wind speed resolution of approximately 0.0018 m/s over a range of ±31 m/s.

Conclusions:

• The novel simulation approach overcomes limitations of traditional lidar calibration methods.
• It enables quantitative identification of optimal operating conditions for coherent wind lidar.
• The method provides high wind speed resolution, meeting calibration requirements for advanced lidar systems.