author = "Moraes, Alison and Sousasantos, Jonas and Paula, Eurico Rodrigues 
                         de and Cunha, Josu{\'e} J{\"u}rgen Popov Pereira da and Lima 
                         Filho, Vicente Carvalho and Vani, Bruno Cesar",
          affiliation = "{Instituto de Aeron{\'a}utica e Espa{\c{c}}o (IAE)} and 
                         {Instituto Tecnol{\'o}gico de Aeron{\'a}utica (ITA)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {McKinsey 
                         \& Company} and {Instituto Tecnol{\'o}gico de Aeron{\'a}utica 
                         (ITA)} and Instituto Federal de Educa{\c{c}}{\~a}o, Ci{\^e}ncia 
                         e Tecnologia de S{\~a}o Paulo (IFSP)",
                title = "Performance analysis of \κ-\μ distribution for Global 
                         Positioning System (GPS) L1 frequency-related ionospheric fading 
              journal = "Journal of Space Weather and Space Climate",
                 year = "2019",
               volume = "9",
               number = "A15",
                month = "may",
             keywords = "ionospheric scintillation, fading distributions, statistical 
                         modeling, GNSS availability, GNSS positioning issues.",
             abstract = "The present work aims to evaluate the application of the kappa-mu 
                         distribution as a representation of the fading effect caused by 
                         the phenomenon of scintillation on L-band transionospheric radio 
                         links. The ionospheric scintillation is a phenomenon defined as a 
                         rapid variation in the amplitude and phase of electromagnetic wave 
                         signals. This phenomenon starts in the first hours of the night, 
                         at latitudes near the geomagnetic equator. Scintillation occurs 
                         when radio signals cross ionospheric irregularities, also known as 
                         plasma bubbles. These plasma bubble structures are generated after 
                         the sunset due to instabilities in the F region of ionosphere. 
                         Distributions with non-single parameter usually present better 
                         results, however, this point requires further investigation by 
                         comparing different models. The goals of this study are: (1) the 
                         modeling of experimental data using the kappa-mu distribution; (2) 
                         the kappa-mu parameters characterization for empirical data and 
                         the evaluation of parameters estimation based in different 
                         approaches; (3) the comparison between the distribution proposed 
                         and other models adopted in the literature in order to verify the 
                         performance of two parameter models. The results of the analysis 
                         performed showed that the kappa-mu distribution presents good 
                         fitting of the empirical scintillation data. These fitting results 
                         were calculated through the chi-square fit test under which the 
                         values reveal fair E[chi(2)] for kappa-mu distribution in most of 
                         the cases. The evaluation of kappa-mu parameters suggests that the 
                         distribution has a more conservative outcome than in the 
                         distributions traditionally used, but being a legitimate 
                         approximation due to its adjustable features in the tail region of 
                         the distribution. Typical pairs of kappa-mu coefficients are 
                         presented for theoretical works. The comparison of kappa-mu 
                         distribution to Rice, Nakagami-m and alpha-mu models showed that 
                         kappa-mu is capable of describing more severe scintillation 
                         scenarios where the tail of the distribution is more raised in 
                         comparison to the other models.",
                  doi = "10.1051/swsc/2019012",
                  url = "http://dx.doi.org/10.1051/swsc/2019012",
                 issn = "2115-7251",
             language = "en",
           targetfile = "swsc180036.pdf",
        urlaccessdate = "25 nov. 2020"