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Doppler profile estimation of MST radar data using multi-parameter cost function

The knowledge of wind velocities at different heights is critical for the study of atmospheric dynamics. Over the last three decades, wind profiler radars have been successfully deployed to obtain altitude profiles of wind velocities with a high temporal resolution. Wind Profilers are coherent pulsed Doppler radars operating in VHF or UHF bands. They estimate the wind velocity with the help of Doppler spectra obtained by analyzing the backscattered signal from the atmospheric radio refractive index fluctuations. As the backscattered signal is weak, accurate estimation of the wind velocity to higher heights require sophisticated signal processing methods and often contribution of human experts. Computation of moments by various statistical methods, fuzzy logic approach and neural network techniques have been reported by a few researchers, which have unique advantages and disadvantages with better performing techniques the mathematical complexity increases manifolds. This paper proposes a wind profile tracing algorithm which traces the wind profile by computationally simple method. The proposed method divides the Doppler spectra into sections of five range-bins each. Then it identifies prospective wind profile `candidate traces'. Certain properties of the Doppler spectrum viz., signal power, spectral width and wind shear, have been parameterized and a `cost function' with non-linear weights is designed. A trace with maximum cost function is selected and the profile is completed maintaining the continuity with the adjacent sections. This method is computationally much simpler compared to contemporary leading methods and shows very encouraging performance on the data of almost all atmospheric conditions. Due to low computational complexity, this method has a high potential for `real-time automated' Doppler profile tracing