Improvement of signal-to-noise ratio for MST radar using weighted semi-parametric algorithm

Abstract

The Indian mesosphere–stratosphere–troposphere (MST) radar is the prominent atmospheric radar that provides the atmospheric movements’ information. The radar data is analyzed to obtain the wind parameter that requires the power spectral estimation. At higher altitudes, the estimation of Doppler spectrum is found to be unsatisfactory using both parametric and nonparametric methods for spectral estimation. In this article, the hyperparameter-free, weighted sparse iterative covariance-based estimation (SPICE) method has been considered. Unlike existing SPICE method, a different hyperparameter–free, weighted SPICE method has been derived using a gradient approach with different step sizes. The two versions of SPICE algorithm, i.e., SPICE a and SPICE b , are applied to the practical MST radar data collected at National Atmospheric Research Laboratory, Gadanki (13.5°N, 79.2°E). The obtained results are evaluated with the existing atmospheric data processor results which use the basic periodogram method. The proposed method shows the significant enhancement in signal-to-noise ratio even at elevated heights.