Estimation of Doppler Profile Using Multiparameter Cost Function Method

Abstract

Wind profilers (WPs) are a special category of ground-based radar instruments used to obtain 3-D profile of wind velocity along the altitude in atmosphere. They transmit radio wave pulses in very high frequency (VHF) or ultrahigh frequency (UHF) bands in vertical and near-vertical directions. The Doppler frequency shift and the time of flight of the echo signals from each beam are measured. These data are analyzed to get the radial velocities of atmospheric targets at all the ranges. The data must be processed from at least three noncoplanar beam directions together to estimate 3-D wind profile. The signal-to-noise ratio is very low for the higher range target echoes. Also, echoes are often contaminated by nonatmospheric signals like clutter, radio frequency interference, and so on. Determining accurate wind profile, especially at higher heights, becomes a challenging task due to these factors. This paper presents a novel algorithm for the estimation of radial velocity profile by processing the set of Doppler power spectra of all range bins. The algorithm identifies prospective atmospheric echoes components. Then it forms velocity profile trails connecting five range bins. The program rejects the profile trails that show velocity change higher than a predefined limit. The remaining trails are evaluated using a specially designed multiparameter cost function (MPCF). The trails with maximum cost are selected and then connected to construct the complete Doppler profile or the radial velocity profile. The key innovation in this method is an improvised function that is created by weighted addition of two terms. The first term is proportional to the signal power, and the second term is a nonlinear function of differential wind shear. This algorithm has been tried on multiple sets of the Indian mesosphere–stratosphere–troposphere radar data and the lower atmospheric WP radar data. The performance of this method is compared with other methods, namely, the adaptive moment estimation method and fuzzy logic approach. It has been observed that the new method shows excellent consistency in extracting the Doppler profile from the power spectral data. This method requires at least 30% lesser computations compared with other methods. The results of the MPCF method showed a very good match with the data obtained from concurrently operated Global Positioning System sonde, an independent wind profiling method. This paper also shows the results on the performance improvement using power spectra from the symmetrical beams. This algorithm shows a great promise as a tool for automatic Doppler profile tracing.