Publication

Accurate nonlinear phase step estimation in phase shifting interferometry

Pramod Rastogi, Abhijit Patil, Rajesh Langoju
2006
Journal Articles

Abstract

We propose a new method for the accurate estimation of nonlinear response of the PZT to the applied voltage. The method uses discrete chirp Fourier transform for the coarse estimation followed by a fine search method for the accurate estimation of the phase step and nonlinearity. The method can be extended to the cases of extraction of multiple phases in the configurations involving multiple PZTs such as holographic moire in the presence of nonlinearity. The robustness of the proposed method is verified by comparing with Cramer-Rao lower bound. Experimental results prove the method's feasibility. (c) 2006 Elsevier B.V. All rights reserved.

Official source

https://infoscience.epfl.ch/entities/publication/dd40492f-92a6-4562-b5fe-72730820d169

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Pramod Rastogi, Abhijit Patil, Rajesh Langoju
2006
Journal Articles

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/dd40492f-92a6-4562-b5fe-72730820d169

About this result

Related concepts (19)

Interferometry

Interferometry is a technique which uses the interference of superimposed waves to extract information. Interferometry typically uses electromagnetic waves and is an important investigative technique in the fields of astronomy, fiber optics, engineering metrology, optical metrology, oceanography, seismology, spectroscopy (and its applications to chemistry), quantum mechanics, nuclear and particle physics, plasma physics, biomolecular interactions, surface profiling, microfluidics, mechanical stress/strain measurement, velocimetry, optometry, and making holograms.

Efficiency (statistics)

In statistics, efficiency is a measure of quality of an estimator, of an experimental design, or of a hypothesis testing procedure. Essentially, a more efficient estimator needs fewer input data or observations than a less efficient one to achieve the Cramér–Rao bound. An efficient estimator is characterized by having the smallest possible variance, indicating that there is a small deviance between the estimated value and the "true" value in the L2 norm sense.

Fisher information

In mathematical statistics, the Fisher information (sometimes simply called information) is a way of measuring the amount of information that an observable random variable X carries about an unknown parameter θ of a distribution that models X. Formally, it is the variance of the score, or the expected value of the observed information. The role of the Fisher information in the asymptotic theory of maximum-likelihood estimation was emphasized by the statistician Ronald Fisher (following some initial results by Francis Ysidro Edgeworth).

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