The technique of calculating the field strength of the ionospheric wave in the very low frequency band based on the wavehop method
Abstract
Introduction: Forecasting the energy parameters of radio tracks is an integral part of planning the operation of radio networks in the very low frequency range. The predicted values of the electric field strength depend on a large number of factors, including the state of the ionosphere and the electrical characteristics of the underlying surface, which are considered using individual components of attenuation multipliers. Particular techniques designed to calculate these components need to be generalized and introduced into the methodology for calculating the energy parameters of radio tracks. Purpose: To develop a wavehop method for calculating the field strength of an ionospheric wave in the very low frequency band with the possibility to enter initial data from the International Reference Ionosphere model and global maps of the electrical characteristics of the underlying surface. Results: We carry out the study using several particular methods related to the calculation of the height of the reflection point of an electromagnetic wave from the ionosphere, the calculation of differential time delays of rays based on the condition of equal elevation angles, and the calculation of reflection coefficients from the Earth's surface and correction antenna coefficients. We develop a technique of calculating the ionospheric wave field strength in the very low frequency band based on the wavehop method. The advanced methodology includes specific techniques for considering the characteristics of the ionosphere using the International Reference Ionosphere model and the characteristics of the underlying surface using appropriate digital maps. We implement the technique as a set of interrelated scripts and functions in the MatLab computing environment. In addition, we perform a series of calculations of the electric field strength of the ionospheric wave for various radio tracks. Comparing predicted values with the results of real measurements we fınd out prediction errors. We conduct statistical studies of prediction errors and confirm the adequacy of the developed technique. Practical relevance: We develop tools that integrate modern achievements in the ionosphere state modeling and digital mapping of the electrical characteristics of the underlying surface into the wavehop method. The implementation of the technique based on the MatLab computing environment makes it possible to reduce the operator's participation at the stage of initial data input and to create opportunities for the development of the autonomous software for predicting the electromagnetic wave field strength in the very low frequency band.
