Forecasting Parameters of Satellite Navigation Signal through Artificial Neural Networks for the Purpose of Civil Aviation
Karolina Krzykowska , Michał Krzykowski
AbstractNavigation 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 is 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 how to facilitate selection of navigation techniques for aircraft operator, taking into account factors determining the accuracy, continuity, availability and integrity of the satellite signal. As a result, the purpose of 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 work indicate further directions of satellite navigation systems development. Due to Authors opinion the researches should focus especially on analysis of real-time satellite signal parameters performance or creating application for UAVs automatically deciding about used technics of navigation.
|Journal series||International Journal of Aerospace Engineering, ISSN 1687-5966, (A 25 pkt)|
|Keywords in English||forecasting, satellite signal, civil aviation, navigation|
|Score||= 25.0, 26-04-2019, ArticleFromJournal|
|Publication indicators||: 2016 = 0.747; : 2017 = 1.182 (2) - 2017=1.329 (5)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.