Monday, 19 August 2019

Spectral Analysis of MST Radar Data via a Sparse Iterative Parameter Estimation Approach

Volume 14 Issue 2 November - January 2019
Research Paper
G. Chandraiah *, T. Sreenivasulu Reddy**
* Research Scholar, Department of Electronics and Communications Engineering, S.V.U. College of Engineering, S.V. University, Tirupati, Andhra Pradesh, India.
** Professor, Department of Electronics and Communications Engineering, S.V.U. College of Engineering, S.V. University, Tirupati, Andhra Pradesh, India.
Chandraiah, G., & Reddy, T. S. (2019). Spectral Analysis of MST Radar Data via a Sparse Iterative Parameter Estimation Approach. i-manager’s Journal on Future Engineering and Technology , 14 (2), 29-36. https://doi.org/10.26634/jfet.14.2.15172
Abstract
The Indian MST radar is sited at National Atmospheric Research Laboratory (NARL), Gadanki, Andhra Pradesh. The MST radar is used to study and characterize the dynamic changes of atmosphere in the regions of Mesosphere, Stratosphere, and Troposphere (MST). MST radar was developed with an active phased antenna array consisting of 1024 Yagi-Uda antenna elements and operated by a frequency of 53 MHz. In this article, a sparse iterative parameter estimation approach for spectral estimation for the radar data has been introduced. Separable models occur normally in spectral analysis, like radar signal processing and astronomy applications. The proposed algorithm for the simulated complex signal which may contain more than one frequency component in presence of noise has been tested. For simulated signal, the algorithm has proven to estimate the power spectrum at low SNR conditions also. Finaly, the proposed algorithm (PALG) has been applied to MST radar data collected on 9 Feb, 2015 to compute Doppler spectrum. After computing Doppler spectrum and Doppler velocities, the wind parameters like Zonal U, Meridional V, and Wind velocity can be calculated from the Doppler velocities. The obtained wind velocity components of the MST radar data is validated through the Global Positioning System (GPS) balloon data.

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