Spectral Peak Estimation for Wind Profiler Radar Based on DWT-OMPCF Algorithm

To address the problem of severe noise and clutter interference affecting the identification of atmospheric echo spectral peaks in wind profiler radar echo power spectra, a wind profiler radar spectral peak estimation method is proposed based on discrete wavelet transform and optimized multi-parameter cost function algorithm in this paper. Differential detection is used to identify and suppress ground clutter in the echo power spectra, and post-validation wavelet parameters are used to denoise the clutter-suppressed echo spectra. A cost function is constructed by introducing parameters such as wind shear threshold, relative spectral power, and normalized differential wind shear. The cost function is then applied to optimize and assign values to Doppler trajectory, enabling the selection of the denoised echo spectral peaks. Experiments using dataset from an atmospheric radiation measurement website demonstrate that compared with various peak estimation methods, the proposed method has better identification performance for atmospheric echo spectral peaks, which can synthesize more accurate atmospheric wind speeds with fewer deviation points and smaller errors.