HF spectrum occupancy and antennas

This paper deals with the research made during the COST 296 action in the WG2, WP 2.3 in the antennas and HF spectrum management fields, focusing the Mitigation of Ionospheric Effects on Radio Systems as the subject of this COST action.info:eu-repo/semantics/publishedVersio

Nowcasting, forecasting and warning for ionospheric propagation: tools and methods

The paper reviews the work done in the course of the COST 271 Action concerned with the development of tools and methods for forecasting, nowcasting and warning of ionospheric propagation conditions. Three broad categories of work are covered. First, the maintenance and enhancement of existing operational services that provide forecast or nowcast data products to end users; brief descriptions of RWC Warsaw and the STIF service are given. Second, the development of prototype or experimental services; descriptions are given of a multi-datasource system for reconstruction of electron density profiles, and a new technique using real-time IMF data to forecast ionospheric storms. The third category is the most wide-ranging, and deals with work that has presented new or improved tools or methods that future operational forecasting or nowcasting system will rely on. This work covers two areas - methods for updating models with prompt data, and improvements in modelling or our understanding of various ionospheric-magnetospheric features - and ranges over updating models of ionospheric characteristics and electron density, modelling geomagnetic storms, describing the spatial evolution of the mid-latitude trough, and validating a recently-proposed technique for deriving TEC from ionosonde observations

Forecasting of ionospheric critical frequency using neural networks

Multilayer perceptron type neural networks (NN) are employed for forecasting ionospheric critical frequency (foF2) one hour in advance. The nonlinear black-box modeling approach in system identification is used. The main contributions: 1. A flexible and easily accessible training database capable of handling extensive physical data is prepared, 2. Novel NN design and experimentation software is developed, 3. A training strategy is adopted in order to significantly enhance the generalization or extrapolation ability of NNs, 4. A method is developed for determining the relative significances (RS) of NN inputs in terms of mapping capability

VARIABILITY OF MIDLATITUDE IONOSPHERIC FOF2 COMPARED TO IMF-POLARITY INVERSIONS

Potential effects of the IMF-orientation on the mid-latitude ionosphere are further investigated using critical frequencies foF2 from six ionosonde stations. For a period of 15 days around each inversion of B-Z, excluding all days with Ap >=6, a quiet standard diurnal variation was determined by day-by-day averaging for each hour UT. The regular diurnal, seasonal and solar cycle variations were then removed from the data by substracting from these the quiet standard value. The so obtained differences ofoF2 were sorted after the INF polarity. Distinct effects of northward and southward inversions were found so that a large part of the day-to day variability may be attributed to IMF B-Z polarity changes

The neural network technique - 1: a general exposition

Near earth space processes are highly complex and nonlinear and mathematical modeling based on first physical principals is usually difficult or impossible. For such cases data driven modeling methods are recommended to be used in parallel with mathematical modeling approach. Highly non-linear processes in the near-earth space are advantageously dealt with using data-driven modeling techniques in the neural network (NN) approach. The only basic requirement for its application is the availability of representative data. (C) 2003 COSPAR. Published by Elsevier Ltd. All rights reserved

Temporal and spatial forecasting of the foF2 values up to twenty four hours in advance

Radio waves of a wide range of frequencies from very low frequency (VLF) to high frequency (HF), (broadly 3 to 30 MHz) can be propagated to great distances via the ionosphere