Spectral Analysis of MST Radar Signal using Maximum Likelihood Estimation Algorithm
G. Madhavi Latha1, G. Chandraiah2, S.Varadarajan3, T.Sreenivasulu Reddy4, P. Satish Kumar5

1G. Madhavi Latha, ECE, S.V. Engineering College, Tirupati, India.
2G. Chandraiah*, ECE, S.V. Engineering College, Tirupati, India.
3S.Varadarajan, ECE, S.V. Engineering College, Tirupati, India.
4T. Sreenivasulu Reddy, Received the B. Tech Degree in ECE from Sri Venkateswara University, Tirupati, India.
5P. Satish Kumar, Professor in ECE Department of ACE Engineering College, Ghatkesar, Hyderabad, India.
Manuscript received on November 27, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 3372-3379 | Volume-9 Issue-2, December, 2019. | Retrieval Number:  B3843129219/2019©BEIESP | DOI: 10.35940/ijeat.B3843.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In this work, we propose Maximum likelihood estimation of low- rank Toeplitz covariance matrix (MELT) with reduced complexity algorithm for computing the power spectral density of mesosphere-stratosphere-troposphere (MST) radar data. MELT is designed based on the method of majorization-minimization and it is an iterative algorithm to update the powers in each successive step. We tested MELT algorithm for complex signal, which contain multiple frequency components in existence of different noise conditions. For simulated complex data, it can be seen that MELT works much better for low Signal to Noise Ratio (SNR) conditions and also effectively detects the frequency components with a fine resolution in the existence with high noise impact. At last, MELT algorithm is applied to the radar data received from MST radar established at National Atmospheric Research laboratory (NARL), Gadhanki. MELT algorithm estimates the accurate Doppler spectra and thus in turn, estimate the wind parameters using Doppler profiles. For the purpose of validation, the obtained radar results through MELT are compared with the Global Positioning System (GPS) radiosonde.
Keywords: Majorization-Minimization (MM) technique, Maximum-likelihood estimation (MLE), Toeplitz matrix, Spectrum estimation, MST Radar and GPS radiosonde.