2015
DOI: 10.1049/iet-map.2014.0312
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Long‐range Loran‐C ground‐wave propagation prediction based on adaptive moving window finite‐difference time‐domain method with compute unified device architecture parallel computing techniques

Abstract: Modelling long-range Loran-C signal propagation numerically is challenging because of its extremely high computational cost. Other analytical/semi-analytical methods are not accurate enough because of unavoidable approximations. In this study, the authors put forward a solution using the adaptive moving window finite-difference time-domain (FDTD) method to compute unified device architecture parallel computing techniques. The moving velocity of the window is dependent upon the wave speed adaptively. To achieve… Show more

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Cited by 12 publications
(2 citation statements)
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References 20 publications
(32 reference statements)
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“…The use of moving window with a pulse excitation source limits processing to the sliding area with the most energy. It is a promising way to accelerate simulations over electrically large domains, with examples including tunnels [55], modelling wave propagation over the ocean [56] (40 m in three dimensions), and the prediction of Loran-C 100 kHz Gaussian modulated pulse ground wave along 400 km long path [57].…”
Section: Large-scale Applicationsmentioning
confidence: 99%
“…The use of moving window with a pulse excitation source limits processing to the sliding area with the most energy. It is a promising way to accelerate simulations over electrically large domains, with examples including tunnels [55], modelling wave propagation over the ocean [56] (40 m in three dimensions), and the prediction of Loran-C 100 kHz Gaussian modulated pulse ground wave along 400 km long path [57].…”
Section: Large-scale Applicationsmentioning
confidence: 99%
“…Many people have used MW-FDTD to solve the EM propagation problem. Yang Xiaoshuan has done a research on EMP propagation in tunnel with MW-FDTD [1], Lili Zhou has done a research on longrange ground-wave propagation with MW-FDTD [2].…”
Section: Introductionmentioning
confidence: 99%