A Refined Phase Unwrapping Method for High Noisy Dense Fringe Interferogram Based on Adaptive Cubature Kalman Filter

Cubature Kalman filter phase unwrapping (CKFPU) is an effective algorithm in unwrapping the interferograms. The local phase slope estimation is a key factor that affects the unwrapped accuracy. However, the estimation accuracy of local phase slop is relatively low in high noisy and dense stripes are...

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Main Authors: Wanli Liu, Jian Shao, Zhenguo Liu, Yang Gao
Format: Article
Language:English
Published: Hindawi Limited 2021-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2021/7141091
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spelling doaj-7a1b8e27aa1c432393179dc3baf2dbbb2021-08-23T01:32:55ZengHindawi LimitedMathematical Problems in Engineering1563-51472021-01-01202110.1155/2021/7141091A Refined Phase Unwrapping Method for High Noisy Dense Fringe Interferogram Based on Adaptive Cubature Kalman FilterWanli Liu0Jian Shao1Zhenguo Liu2Yang Gao3School of Mathematics and StatisticsSchool of Physics and New EnergySchool of Transportation EngineeringInternational Digital LaboratoryCubature Kalman filter phase unwrapping (CKFPU) is an effective algorithm in unwrapping the interferograms. The local phase slope estimation is a key factor that affects the unwrapped accuracy. However, the estimation accuracy of local phase slop is relatively low in high noisy and dense stripes areas, which usually leads to the unsatisfactory unwrapped results. In order to effectively solve this issue, the rewrapped map of the unwrapped phase (obtained by CKFPU algorithm), which is a filtered interferogram with clearer fringes and more detailed information, is proposed in this paper to improve the phase slope estimation. In order to solve the problem of imprecise error variance for the new phase slope estimation, an adaptive factor is introduced into the CKFPU algorithm to increase the stability and reliability of the phase unwrapping algorithm. The proposed method is compared with the standard CKFPU algorithm using both simulated and real data. The experimental results validate the feasibility and superiority of the proposed method for processing those high noise dense fringe interferograms.http://dx.doi.org/10.1155/2021/7141091
collection DOAJ
language English
format Article
sources DOAJ
author Wanli Liu
Jian Shao
Zhenguo Liu
Yang Gao
spellingShingle Wanli Liu
Jian Shao
Zhenguo Liu
Yang Gao
A Refined Phase Unwrapping Method for High Noisy Dense Fringe Interferogram Based on Adaptive Cubature Kalman Filter
Mathematical Problems in Engineering
author_facet Wanli Liu
Jian Shao
Zhenguo Liu
Yang Gao
author_sort Wanli Liu
title A Refined Phase Unwrapping Method for High Noisy Dense Fringe Interferogram Based on Adaptive Cubature Kalman Filter
title_short A Refined Phase Unwrapping Method for High Noisy Dense Fringe Interferogram Based on Adaptive Cubature Kalman Filter
title_full A Refined Phase Unwrapping Method for High Noisy Dense Fringe Interferogram Based on Adaptive Cubature Kalman Filter
title_fullStr A Refined Phase Unwrapping Method for High Noisy Dense Fringe Interferogram Based on Adaptive Cubature Kalman Filter
title_full_unstemmed A Refined Phase Unwrapping Method for High Noisy Dense Fringe Interferogram Based on Adaptive Cubature Kalman Filter
title_sort refined phase unwrapping method for high noisy dense fringe interferogram based on adaptive cubature kalman filter
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1563-5147
publishDate 2021-01-01
description Cubature Kalman filter phase unwrapping (CKFPU) is an effective algorithm in unwrapping the interferograms. The local phase slope estimation is a key factor that affects the unwrapped accuracy. However, the estimation accuracy of local phase slop is relatively low in high noisy and dense stripes areas, which usually leads to the unsatisfactory unwrapped results. In order to effectively solve this issue, the rewrapped map of the unwrapped phase (obtained by CKFPU algorithm), which is a filtered interferogram with clearer fringes and more detailed information, is proposed in this paper to improve the phase slope estimation. In order to solve the problem of imprecise error variance for the new phase slope estimation, an adaptive factor is introduced into the CKFPU algorithm to increase the stability and reliability of the phase unwrapping algorithm. The proposed method is compared with the standard CKFPU algorithm using both simulated and real data. The experimental results validate the feasibility and superiority of the proposed method for processing those high noise dense fringe interferograms.
url http://dx.doi.org/10.1155/2021/7141091
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