ENHANCED AUTOCORRELATION TECHNIQUES IN DOPPLER WIND LIDAR SYSTEMS FOR IMPROVED VELOCITY MEASUREMENTS

Abstract

This research investigates methods for enhancing autocorrelation features within Doppler Wind LIDAR systems to improve the accuracy of wind velocity measurements. Using signal processing techniques and simulation tools such as Optic-System, the work aims to minimize noise effects on power spectral density (PSD) estimation. Experimental findings reveal enhanced accuracy in wind profiling, reduction in computational time, and increased system reliability, making this approach valuable for advancing atmospheric science and promoting efficient use of renewable energy sources.