Ionosphere Model Development using Regression Method

Abstract

For earth survival an ionosphere is most important and utmost noteworthy for vital satellite communiqué for the navigation positioning exactness persistence. It encompasses different number of layers subject to the quantity of electron density based on distance. So many ionospheric models of its kind are available to guess electron density with temporal determinations based on different research done within this era. GPS data are habitually castoff in these models. Because of that the essentiality is, a required of progressing ionospheric models to cope up with dissimilar time period for low latitudes of nation. Apart from this, an ionospheric tomography is not a well-posed problem. Ionospheric TEC bring into being concurrently in copious locations, which can be determined by a number of methods to overcome electron density. This paper is projected for the research of developing a method to estimate of total electron density which cover entire Indian region. Largely we can utilized satellite data and placed together by number of calculations. The organization of massive figures are intended the usage of data mining algorithms, and artificial neural network algorithms intended to guesstimate. A thorough study on ionospheric model development using regression method and further proposed idea based on literature can be seen in current research paper.