Aviation Carbon Neutrality Achieving by Wind Lidar Retrieval Algorithm Based on Multi-core CT-LSM

To counteract the limitations inherent in the Vaisala laser wind measurement radar data processing system specifically, the issue of missing critical data and the challenge of achieving high spatiotemporal resolution, this study has integrated advanced machine learning techniques. We have developed a sophisticated mathematical model for the civil aviation meteorological laser wind measurement radar data processing system. This model encompasses a comprehensive suite of algorithms designed for data retrieval, moderate extrapolation, and the development of a laser wind measurement radar retrieval algorithm that leverages a graphical display engine. The core of this innovation is the application of a nonlinear fitting technique grounded in the Multi Core CT-Liquid State Machine (Multi Core CT-LSM), a cutting-edge technology tailored for multi-core radar systems. The successful deployment of this algorithm in the data processing workflow of the Lanzhou Zhongchuan Airport’s laser wind measurement radar has yielded promising outcomes. It has notably contributed to enhancing the spatiotemporal resolution of three-dimensional wind field detection, thereby providing substantial improvements to the meteorological support systems at civil aviation airports.