14 April 2017 Dynamic interference fringe processing algorithms based on non-linear optimization
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Proceedings Volume 10337, Saratov Fall Meeting 2016: Laser Physics and Photonics XVII; and Computational Biophysics and Analysis of Biomedical Data III; 103370S (2017) https://doi.org/10.1117/12.2267985
Event: Saratov Fall Meeting 2016: Fourth International Symposium on Optics and Biophotonics, 2016, Saratov, Russian Federation
Abstract
The paper deals with an approach to dynamic parameters estimation of interferometric signals based on non-linear optimization technique. The features of the approach are demonstrated on the example of the gradient descent method as simple iterative non-linear optimization algorithm. The possibilities of using this approach to refine the signal parameters estimates obtained by the extended Kalman filter are considered. The model of one-dimensional interferometric signal is presented. The results of simulated signals processing are analyzed. It was investigated how the quantity of gradient descent iterations influences the quality of parameters estimation. It is shown that the gradient descent provides 65% increase of signal-to-noise ratio for reconstructed signal in comparison with original signal. The proposed method in combination with the extended Kalman filter allows to decrease the amplitude estimation error compared to the unmodified extended Kalman filter. The processing time evaluation results are presented. The recommendations on using proposed approach for interferometric data processing are given.
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Petr A. Ermolaev, Petr A. Ermolaev, Maxim A. Volynsky, Maxim A. Volynsky, Anna S. Tomarzhevskaya, Anna S. Tomarzhevskaya, } "Dynamic interference fringe processing algorithms based on non-linear optimization", Proc. SPIE 10337, Saratov Fall Meeting 2016: Laser Physics and Photonics XVII; and Computational Biophysics and Analysis of Biomedical Data III, 103370S (14 April 2017); doi: 10.1117/12.2267985; https://doi.org/10.1117/12.2267985
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