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Proceedings Paper

Noise-immune phase-shifting interferometric system based on Markov nonlinear filtering method
Author(s): Igor P. Gurov; D. V. Sheynikhovich
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Paper Abstract

In precise measurement of objects geometric characteristics are widely used the phase-shifting interferometric systems. Simple data processing algorithms are usually realized, but it is difficult to optimize such systems for accuracy increasing on general totality of measured data because of nonlinear data transformation. Besides that an important problem is the noise-immune phase unwrapping on intervals more than 27t rad. Proposed interferometric system is free from these disadvantages. In the system new method and algorithm of phase estimation are realized, which are based on Markov theory of optimal non-linear filtering. The main advantages of proposed system are the following: data processing in real time scale, solving the phase unwrapping problem and minimization of phase errors in conditions of influence of phase fluctuations and noise correlated with the signal. Phase restoration error in typical measurement conditions does not exceed 0. 15 rad. on criterion peakvalley, while rms-error does not exceed 0.05 rad. The system provides the possibility to solve the synthesis and optimization problems of wide class of multidimensional, unstationary and non-linear systems

Paper Details

Date Published: 8 October 1996
PDF: 5 pages
Proc. SPIE 2823, Statistical and Stochastic Methods for Image Processing, (8 October 1996); doi: 10.1117/12.253454
Show Author Affiliations
Igor P. Gurov, St. Petersburg Institute of Fine Mechanics and Optics (Russia)
D. V. Sheynikhovich, St. Petersburg Institute of Fine Mechanics and Optics (Russia)

Published in SPIE Proceedings Vol. 2823:
Statistical and Stochastic Methods for Image Processing
Edward R. Dougherty; Francoise J. Preteux; Jennifer L. Davidson, Editor(s)

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