| dc.identifier.citation | Zakharenko, V., Kharlanova, V., Ryabov, V., Yerin, S., Brazhenko, A., Fransuzenko, A., Konovalenko, O., Ground support of Juno mission and RFI mitigation. In Fischer, G., Jackman, C. M., Louis, C. K., Sulaiman, A. H., Zucca, P., Dublin Institute for Advanced Studies (Eds.), Planetary, Solar and Heliospheric Radio Emissions IX, 2023. https://doi.org/10.25546/103685 | |
| dc.description.abstract | Joint observations provide much more useful data and improve the quality of the analysis. But to obtain high-quality results, it is often necessary to improve the algorithms of the processing program. Radio frequency interference (RFI) is non-stationary, multi-scale in time and frequency, and therefore sometimes difficult to distinguish from the powerful radiation sources we study (Jupiter and the Sun). The anti-interference algorithms used to remove the RFI are not universal for all telescopes, often resulting in unique sets of programs being developed for each situation. Additionally, many new approaches are currently being developed, such as various statistical methods, using artificial intelligence, and neural networks to address this issue. The paper describes new algorithms for distinguishing the radiation of cosmic sources from radio frequency interference with the aid of adjustable parameters of intensity, time and bandwidth. | |
