A Novel Image Preprocessing Algorithm for Doppler Wind Spectrum Inversion: Principle, Method, and Performance

We propose a novel image preprocessing algorithm (IPA) for coherent Doppler wind lidar (CDWL) wind spectrum inversion under low signal-to-noise ratio (SNR) conditions. By utilizing prior knowledge such as the spatial continuity of wind spectra, this new algorithm significantly improves the reliability of the peak frequency estimation and enhances the wind inversion accuracy and precision. The theoretical analysis shows that the IPA can improve the accuracy and precision of the wind spectrum inversion under low SNR, through preselecting and weighting the Doppler wind spectra. Verified by simulation and real CDWL measurements, the IPA effectively enhances the accuracy and reliability of lidar wind spectrum inversion under low SNR conditions. Specifically, the performance enhancement is equivalent to an approximate improvement in the SNR of the data by 2.5 and 5 dB. The measurements with real CDWL measurements show the maximum effective detection range can be increased by more than 2 km. The IPA is low complexity, demanding low computation resources, and can be applied to high temporal resolution Doppler wind estimation.