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

Accurate wind speed measurement in coherent wind lidar systems fundamentally depends on proper calibration. Traditional flywheel-based calibration measures the speed of hard targets but suffers from a five-order-of-magnitude discrepancy compared to aerosol backscatter, making it difficult to simulate realistic atmospheric return signals. Alternatively, wind cups provide atmospheric wind speed measurements but rely on specific wind conditions that are inherently unpredictable and often require extended waiting periods. These limitations significantly hinder the effectiveness of both methods for precise system calibration. To overcome these challenges, this study proposes a method for simulating atmospheric wind speed profiles and aerosol scenarios to validate coherent wind lidar performance. In this approach, backscatter signal intensity is simulated using amplitude modulation (AM), while wind speed variations with altitude are simulated using frequency modulation (FM). The proposed method is suitable for validating and optimizing coherent wind lidar performance, including measurement accuracy, wind speed resolution, and retrieval algorithms. The study also investigates the influence of aerosol backscatter intensity on wind speed retrieval accuracy. Results indicate that wind speed retrieval errors increase when the carrier-to-noise ratio (CNR) is either too high or too low. The method enables quantitative identification of the optimal CNR value, which increases with wind speed. Furthermore, the proposed approach achieves a wind speed resolution of approximately 0.0018 m/s across a range of ±31 m/s, meeting the specific requirements for coherent wind lidar calibration.