@Article{LopesAntFohKriKug:2023:IoScMi,
               author = "Lopes, Rafael Anderson Martins and Antreich, Felix and 
                         Fohlmeister, Friederike and Kriegel, Martin and Kuga, Helio 
                         Koiti",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Tecnol{\'o}gico de Aeron{\'a}utica (ITA)} and {German Aerospace 
                         Center (DLR)} and {German Aerospace Center (DLR)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Ionospheric Scintillation Mitigation with Kalman PLLs Employing 
                         Radial Basis Function Networks",
              journal = "IEEE Transactions on Aerospace and Electronic Systems",
                 year = "2023",
               volume = "59",
               number = "5",
                pages = "6878--6893",
                month = "Oct.",
             keywords = "Amplitude and phase estimation, global navigation satellite system 
                         (GNSS), ionospheric scintillation mitigation, Kalman phase-locked 
                         loop (PLL), radial basis function (RBF) networks.",
             abstract = "We investigate two adaptive Kalman phase-locked loop (PLL) 
                         structures for ionospheric scintillation mitigation for global 
                         navigation satellite systems receivers, employing radial basis 
                         function (RBF) networks to model the scintillation phase and 
                         amplitude, instead of the typically employed autoregressive (AR) 
                         models. In the first structure, the Kalman filter innovations are 
                         computed by the arctangent phase discriminator, and the state 
                         estimates are directly employed in the carrier replica generation. 
                         In the second structure, the Kalman filter measurements are the 
                         prompt correlator outputs, and the error states are computed and 
                         used by a state feedback controller to provide a control signal to 
                         drive the carrier replica generation. The nonlinear RBFs provide 
                         more flexibility to capture nonlinear dynamics evolving with time, 
                         possibly present in the scintillation phase and amplitude. The 
                         weights of the RBF networks and the covariance matrices of the 
                         process and measurement noise of the Kalman filters are estimated 
                         online in the adaptive Kalman PLL structures. Simulations with 
                         synthetic severe scintillation data show the capability of the 
                         proposed Kalman PLLs to improve robustness to scintillation 
                         effects in carrier synchronization, with performance similar to 
                         the corresponding structures employing AR scintillation models. 
                         Simulations using recorded scintillation data collected by a 
                         commercial receiver highlight the learning and generalization 
                         capability of the RBF networks to cope with evolving scintillation 
                         characteristics over time with possibly nonlinear effects. The 
                         Kalman PLL structures employing the RBF networks present reduced 
                         errors compared with the structures using AR models.",
                  doi = "10.1109/TAES.2023.3281431",
                  url = "http://dx.doi.org/10.1109/TAES.2023.3281431",
                 issn = "0018-9251",
             language = "en",
           targetfile = "
                         
                         Ionospheric_Scintillation_Mitigation_With_Kalman_PLLs_Employing_Radial_Basis_Function_Networks.pdf",
        urlaccessdate = "28 abr. 2024"
}