УДК: 681.3.01, 681.787
Comparative analysis of extended Kalman filtering and the sequential Monte Carlo method, using probability models of signals in optical coherent tomography
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Волынский М.А., Гуров И.П., Ермолаев П.А., Скаков П.С. Сравнительный анализ расширенной фильтрации Калмана и последовательного метода Монте-Карло при использовании вероятностных моделей сигналов в оптической когерентной томографии // Оптический журнал. 2015. Т. 82. № 8. С. 54–60.
Volynskiy M.A., Gurov I.P., Ermolaev P.A., Skakov P.S. Comparative analysis of extended Kalman filtering and the sequential Monte Carlo method, using probability models of signals in optical coherent tomography [in Russian] // Opticheskii Zhurnal. 2015. V. 82. № 8. P. 54–60.
M. A. Volynskiĭ, I. P. Gurov, P. A. Ermolaev, and P. S. Skakov, "Comparative analysis of extended Kalman filtering and the sequential Monte Carlo method, using probability models of signals in optical coherent tomography," Journal of Optical Technology. 82(8), 533-537 (2015). https://doi.org/10.1364/JOT.82.000533
This paper describes signals in optical coherent tomography using probability models and presents a comparative analysis of an extended Kalman filter and the sequential Monte Carlo method for dynamic estimation of the signal parameters. The results of a comparison of the estimation errors and the response rate of the algorithms are presented. It is shown that the quality of the images formed by means of an extended Kalman filter and the sequential Monte Carlo method depends on the available a priori information concerning the characteristics of the data to be processed. Recommendations are made of the use of signal-processing algorithms in correlation optical coherent tomography.
probability models, extended Kalman filter, sequential Monte Carlo method, optical coherent tomography
Acknowledgements:This work was carried out with the financial support of the Ministry of Education and Science of the Russian Federation.
OCIS codes: 110.4500, 120.3180, 120.2650, 100.2000, 100.3175
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