Upgrading CCIR'sfoF2maps using available ionosondes and genetic algorithms

Abstract

We have developed a new approach towards a new database of the ionospheric parameter o 2. This parameter, being the frequency of the maximum of the ionospheric electronic density profile and its main modeller, is of great interest not only in atmospheric studies but also in the realm of radio propagation. The current databases, generated by CCIR (Committee Consultative for Ionospheric Radiowave propagation) and URSI (International Union of Radio Science), and used by the IRI (International Reference Ionosphere) model, are based on Fourier expansions and have been built in the 60s from the available ionosondes at that time. The main goal of this work is to upgrade the databases by using new available ionosonde data. To this end we used the IRI diurnal/spherical expansions to represent the o 2 variability, and computed its coefficients by means of a genetic algorithm (GA). In order to test the performance of the proposed methodology, we applied it to the South American region with data obtained by RAPEAS (Red Argentina para el Estudio de la Atmósfera Superior, i.e. Argentine Network for the Study of the Upper Atmosphere) during the years 1958 to 2009. The new GA coefficients provide a global better fit of the IRI model to the observed o 2 than the CCIR coefficients. Since the same formulae and the same number of coefficients were used, the overall integrity of IRI's typical ionospheric feature representation was preserved. The best improvements with respect to CCIR are obtained at low solar activities, at large (in absolute value) modip latitudes, and at night-time. The new method is flexible in the sense that can be applied either globally or regionally. It is also very easy to recompute the coefficients when new data is available. The computation of a third set of coefficients corresponding to days of medium solar activity in order to avoid the interpolation between low and high activities is suggested.The same procedure as for o 2 can be perfomed to obtain the ionospheric parameter M(3000)F2 .

Adjusting CCIR Maps to Improve Local Behaviour of Ionospheric Models

“…Based on our approach, the system modifies the coefficients and not the structure of the CCIR files, which is fully preserved. Efforts to improve the performance without violating the structure of CCIR files has been examined by past studies [26]. This concept is feasible as we are aiming towards an exclusively local improvement (over the area of Cyprus).…”

A Psychovisual Optimization of Wavelet Foveation-Based Image Coding and Quality Assessment Based on Human Quality Criterions

“…We plan to assess the identified differences among a candidate and reference pictures and embrace instinctive measures. We expect the utilization of Fränti conditions [40][41] required for this assessment experimentation, as suggested in the CCIR recommendation detailed in [42][43] and summarized in Table. 4. Assuming that these conditions are regarded, we standardize the assessment range to evade extra blunders environment dependent.…”