Hybrid window functions: Signal to noise ratio improvement of mst radar signals

In this paper the effect of window shape parameter ‘α’ in Hybrid window functions on the signal to noise ratio (SNR) values of the Indian Mesosphere-Stratosphere-Troposphere (MST) radar is computed. The six parts of multibeam observations of the lower atmosphere made by the MST radar are utilized for the analysis of results. Prior to the Fourier transformation, the in-phase and quadrature components of radar echo samples are weighted with proposed Hybrid windows based on the Kaiser-Hamming, Cosh-Hamming, Hann-Poisson and Kaiser Window functions. The effects of data weighting with the change of the window shape parameter ‘α’ of the Hybrid Window functions are given in it. It is noted that the increase of variable window shape parameter ‘α’ increases the signal to noise ratio values and a better improvement is reported. For Hybrid Window functions are proposed to analyze the MST radar return signals to obtain optimum values of the window shape parameter. The results shows the improvement of signal to noise ratio of noisy data due to the effect of side lobe reduction and demands for the design of the optimal window functions.