Forecasting Parameters of Satellite Navigation Signal through Artificial Neural Networks for the Purpose of Civil Aviation

Abstract

Navigation is a key element influencing fluent, rapid, and safe transport of people and goods. During the last years, special attention was paid to satellite navigation, which is a part of radionavigation where positioning is done thanks to artificial satellites. Issues of application and development of satellite navigation systems in civil aviation are the subject of numerous research and scientific studies in the world. The quality of satellite signal determined by parameters such as accuracy, continuity, availability, and integrity determines possibility of its operational use. Particular attention of scientific research is therefore devoted to the requirements and limitations imposed on satellite systems prior to their implementation in aviation. This extremely important aspect justified undertaking of the aforementioned problem in this article. The paper attempts to answer the question on how to facilitate selection of navigation techniques for the aircraft operator, taking into account factors determining the accuracy, continuity, availability, and integrity of the satellite signal. As a result, the purpose of the work was defined as development of a method for forecasting the values of satellite navigation signal parameters used in air transport by artificial neural networks, taking into account selected atmospheric conditions. Results included in the work indicate further directions of satellite navigation system development. Due to authors’ opinion, the researches should focus especially on the analysis of real-time satellite signal parameter performance or creating applications for UAVs automatically deciding about used techniques of navigation.