Open Access Open Access  Restricted Access Subscription Access

Application of Multiple Signal Classification Algorithm on GPS TEC for Earthquakes


Affiliations
1 K L University, Green fields, Vaddeswaram - 522502, Andhra Pradesh, India
 

Background/Objectives: Earthquakes are the more vulnerable disasters for mankind and are inevitable. The major objective of our work is to identify the precursors of earthquakes and analysed the precursors in ionosphere prior to the occurrence of earthquake using Global Positioning System Total Electronic Content (GPSTEC). Methods/Statistical Analysis: In this work Multiple Signal Classification algorithm (MUSIC) is explored. MUSIC estimates the frequency content of a signal or autocorrelation matrix using a Eigen space method. Findings: It is clearly observed that there is a significant raise in energy of the ionosphere on the day of earthquake occurrence. Application/Improvement: If the quality data is available before and after the occurrence of earthquake also, then it may be possible to develop the early warning system for earthquakes.

Keywords

Earthquakes, GPSTEC, Ionosphere, Multiple Signal Classification (MUSIC), Seismo-ionospheric Perturbations.
User

Abstract Views: 188

PDF Views: 0




  • Application of Multiple Signal Classification Algorithm on GPS TEC for Earthquakes

Abstract Views: 188  |  PDF Views: 0

Authors

S. K. Baji
K L University, Green fields, Vaddeswaram - 522502, Andhra Pradesh, India
K. S. Ramesh
K L University, Green fields, Vaddeswaram - 522502, Andhra Pradesh, India
R. Revathi
K L University, Green fields, Vaddeswaram - 522502, Andhra Pradesh, India
S. Koteswara Rao
K L University, Green fields, Vaddeswaram - 522502, Andhra Pradesh, India

Abstract


Background/Objectives: Earthquakes are the more vulnerable disasters for mankind and are inevitable. The major objective of our work is to identify the precursors of earthquakes and analysed the precursors in ionosphere prior to the occurrence of earthquake using Global Positioning System Total Electronic Content (GPSTEC). Methods/Statistical Analysis: In this work Multiple Signal Classification algorithm (MUSIC) is explored. MUSIC estimates the frequency content of a signal or autocorrelation matrix using a Eigen space method. Findings: It is clearly observed that there is a significant raise in energy of the ionosphere on the day of earthquake occurrence. Application/Improvement: If the quality data is available before and after the occurrence of earthquake also, then it may be possible to develop the early warning system for earthquakes.

Keywords


Earthquakes, GPSTEC, Ionosphere, Multiple Signal Classification (MUSIC), Seismo-ionospheric Perturbations.



DOI: https://doi.org/10.17485/ijst%2F2016%2Fv9i17%2F132835