A Refined Phase UnwrappingMethod for High Noisy Dense Fringe Interferogram Based on Adaptive Cubature Kalman Filter
A Refined Phase UnwrappingMethod for High Noisy Dense Fringe Interferogram Based on Adaptive Cubature Kalman Filter
复制标题
基于自适应容积卡尔曼滤波器的高噪声密集条纹干涉图精细化相位展开方法
DOI：
10.1155/2021/7141091
复制
发表时间：
2021
影响因子：
--
通讯作者：
Yang Gao
中科院分区：
文献类型：
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作者：
Wanli Liu;Jian Shao;Zhenguo Liu;Yang Gao
立方卡尔曼滤波相位解缠（CKFPU）是一种有效的干涉图解缠算法。局部相位斜率估计是影响解缠精度的关键因素。然而，在高噪声和密集条纹区域，局部相位斜率的估计精度相对较低，这通常会导致解包裹结果不理想。为了有效地解决这一问题，本文提出了对CKFPU算法得到的解缠相位进行重缠，得到条纹更清晰、信息更详细的滤波干涉图，从而提高相位斜率的估计精度。为了解决新相位斜率估计误差方差不精确的问题，在CKFPU算法中引入自适应因子，提高了相位解缠算法的稳定性和可靠性。该方法与标准CKFPU算法进行了比较，使用模拟和真实的数据。实验结果验证了该方法对高噪声密集条纹干涉图处理的可行性和优越性。
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.