Robust phase unwrapping algorithm for interferometric applications based on Zernike polynomial fitting and Wrapped Kalman Filter

2022 ◽  
Vol 152 ◽  
pp. 106952
Author(s):  
Zixin Zhao ◽  
Junxiang Li ◽  
Chen Fan ◽  
Yijun Du ◽  
Menghang Zhou ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Phase Unwrapping ◽  
Polynomial Fitting ◽  
Zernike Polynomial

2D phase unwrapping algorithm for interferometric applications based on derivative Zernike polynomial fitting technique

2014 ◽  
Vol 26 (1) ◽  
pp. 017001 ◽  
Author(s):  
Zixin Zhao ◽  
Hong Zhao ◽  
Lu Zhang ◽  
Fen Gao ◽  
Yuwei Qin ◽  
...  
Keyword(s):  
Phase Unwrapping ◽  
Polynomial Fitting ◽  
Zernike Polynomial

Robust phase unwrapping algorithm based on Zernike polynomial fitting and Swin-Transformer network

2022 ◽  
Author(s):  
Zixin Zhao ◽  
Menghang Zhou ◽  
Yijun Du ◽  
Junxiang Li ◽  
Chen Fan ◽  
...  
Keyword(s):  
Speckle Pattern ◽  
Phase Unwrapping ◽  
Electronic Speckle Pattern Interferometry ◽  
Polynomial Fitting ◽  
Regression Problem ◽  
Phase Measurements ◽  
Zernike Polynomial ◽  
Polynomial Coefficients ◽  
Open Issue ◽  
The Relationship

Abstract Phase unwrapping plays an important role in optical phase measurements. In particular, phase unwrapping under heavy noise conditions remains an open issue. In this paper, a deep learning-based method is proposed to conduct the phase unwrapping task by combining Zernike polynomial fitting and a Swin-Transformer network. In this proposed method, phase unwrapping is regarded as a regression problem, and the Swin-Transformer network is used to map the relationship between the wrapped phase data and the Zernike polynomial coefficients. Because of the self-attention mechanism of the transformer network, the fitting coefficients can be estimated accurately even under extremely harsh noise conditions. Simulation and experimental results are presented to demonstrate the outperformance of the proposed method over the other two polynomial fitting-based methods. This is a promising phase unwrapping method in optical metrology, especially in electronic speckle pattern interferometry.

scholarly journals A Mobile Localization Method in Smart Indoor Environment Using Polynomial Fitting for Wireless Sensor Network

2020 ◽  
Vol 2020 ◽  
pp. 1-17 ◽  
Author(s):  
Yan Wang ◽  
Yang Yan ◽  
Zhengjian Li ◽  
Long Cheng
Keyword(s):  
Kalman Filter ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Indoor Environment ◽  
Detection Threshold ◽  
Superior Performance ◽  
Wireless Sensor ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Polynomial Fitting

The main factor affecting the localization accuracy is nonline of sight (NLOS) error which is caused by the complicated indoor environment such as obstacles and walls. To obviously alleviate NLOS effects, a polynomial fitting-based adjusted Kalman filter (PF-AKF) method in a wireless sensor network (WSN) framework is proposed in this paper. The method employs polynomial fitting to accomplish both NLOS identification and distance prediction. Rather than employing standard deviation of all historical data as NLOS detection threshold, the proposed method identifies NLOS via deviation between fitted curve and measurements. Then, it processes the measurements with adjusted Kalman filter (AKF), conducting weighting filter in the case of NLOS condition. Simulations compare the proposed method with Kalman filter (KF), adjusted Kalman filter (AKF), and Kalman-based interacting multiple model (K-IMM) algorithms, and the results demonstrate the superior performance of the proposed method. Moreover, experimental results obtained from a real indoor environment validate the simulation results.

Goodness-of-prediction of Zernike polynomial fitting to corneal surfaces

2005 ◽  
Vol 31 (12) ◽  
pp. 2350-2355 ◽  
Author(s):  
Michael K. Smolek ◽  
Stephen D. Klyce
Keyword(s):  
Polynomial Fitting ◽  
Zernike Polynomial

scholarly journals InSAR Phase Unwrapping Based on Square-Root Cubature Kalman Filter

2020 ◽  
Vol 13 ◽  
pp. 4627-4641
Author(s):  
Xiaomei Luo ◽  
Hongtao Li ◽  
Zhilong Dong ◽  
Shengqi Zhu
Keyword(s):  
Kalman Filter ◽  
Phase Unwrapping ◽  
Square Root ◽  
Cubature Kalman Filter

Absolute subaperture testing by multiangle averaging and Zernike polynomial fitting method

2013 ◽  
Vol 52 (8) ◽  
pp. 085101 ◽  
Author(s):  
Fengtao Yan ◽  
Bin Fan ◽  
Xi Hou ◽  
Fan Wu
Keyword(s):  
Polynomial Fitting ◽  
Zernike Polynomial ◽  
Fitting Method

scholarly journals Adaptive Unscented Kalman Filter Phase Unwrapping Method and Its Application on Gaofen-3 Interferometric SAR Data

Sensors ◽  
2018 ◽  
Vol 18 (6) ◽  
pp. 1793 ◽  
Author(s):  
Yandong Gao ◽  
Shubi Zhang ◽  
Tao Li ◽  
Qianfu Chen ◽  
Shijin Li ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Unscented Kalman Filter ◽  
Phase Unwrapping ◽  
Adaptive Unscented Kalman Filter ◽  
Sar Data ◽  
Interferometric Sar
Sign in / Sign up

Export Citation Format

Share Document