Developing an ANN electron density profile model over Cyprus based on ionosonde measurements

The impact of the upper atmosphere on navigation, communication as well as surveillance systems is defined by the state of the ionosphere and in particular by variations in its electron density profile along the signal propagation path. The requirement for the accurate specification of the electron density profile stems from the fact that the electron density at each altitude determines the refractive index for radiowaves that are refracted by or penetrate the ionosphere and therefore affects significantly navigation and communication signals. Consequently satellite systems that are based on trans-ionospheric propagation may be affected by complex variations in the ionospheric structure in space and time leading to degradation of the availability, accuracy and reliability of their services. Therefore the specification of the electron density profile over a geographical region is very important within the context of operation of such systems. Although regional models have been developed for such a purpose by interpolating data coming from different instruments using various techniques, for a limited geographical scope, the single station model approach is the preferable option as it best encapsulates the behaviour of the ionosphere over the station. This paper presents the development of an Artificial Neural Network (ANN) model for the electron density profile of the ionosphere over Cyprus based on manually scaled ionograms collected at the Nicosia ionosonde station during the period 2009-2013.