Implementing PCA on MST Radar data for Wind Analysis - Anitha, M; Avanija, J (International Journal of Computer Sciences and Engineering, 2025)
The data collected from MST radar uses traditional and statistical analysis for inferring wind components from the spectral data. There are several algorithms available for dimensionality reduction on big data using PCA. These algorithms are non -parametric and often implemented on high dimensional datasets. It will be quite interesting to use these analytical algorithms in the context of MST radar dataset. The existing algorithms are very week in estimation of Doppler at low SNR conditions at higher altitudes. Thus PCA algorithm has been applied on the MST Radar data to find Power Spectrum (PS) and from Power Spectrum Doppler Frequency components are estimated. The components are Zonal (U), Meridional (V), Windspeed (W) are estimated from Doppler Frequency. The PCA derived wind data has to be qualified with wind information from GPS radio-sonde thereafter