An Efficient Algorithm for Improved Doppler Profile Detection of MST Radar Signals

Abstract. An efficient algorithm based on Empirical Mode Decomposition (EMD) de-noising using soft threshold techniques for accurate doppler profile detection and Signal to Noise Ratio (SNR) improvement of MST Radar Signals is discussed in this paper. Hilbert Huang Transform (HHT) is a time-frequency analysis technique for processing radar echoes which constitutes EMD process that decomposes the non-stationary signals into Intrinsic Mode Functions (IMFs). HHT process has been applied on the time series data of MST (Mesosphere-Stratosphere–Troposphere) radar collected from NARL (National Atmospheric research Laboratory), Gadanki, India. Further, spectral moments were estimated and signal parameters such as mean doppler, signal power, noise power and SNR were calculated. Stacked doppler profile was plotted to observe the improvement in doppler detection. It has been observed that there is a considerable improvement in recognition of the doppler echo leading to improved Signal Power and SNR. The algorithm was tested for its efficacy on various data sets for all the 6 beams and the results of two data sets are presented.