Enhanced multi-baseline unscented Kalman filtering phase unwrapping algorithm
Enhanced multi-baseline unscented Kalman filtering phase unwrapping algorithm
复制标题
增强型多基线无迹卡尔曼滤波相位展开算法
DOI：
10.1109/jsee.2016.00035
复制
发表时间：
2016-04
影响因子：
2.1
通讯作者：
Xie, Xianming
中科院分区：
文献类型：
--
作者：
Xie, Xianming
本文提出了一种基于修正矩阵束模型的联合相位梯度估计器与无迹卡尔曼滤波相结合的多基线相位解缠算法，以及一种基于相位质量估计函数的最优路径跟踪策略。改进的联合相位梯度估计器能够准确有效地从含噪干涉图中提取包裹像元的相位梯度信息，大大提高了该方法的性能。最优路径跟踪策略保证了该算法能够沿着高依赖像素到低依赖像素同时进行噪声抑制和相位展开。因此，所提出的算法可以被预测为相对于一些其他算法获得更好的结果，如将由从合成数据获得的结果所证明的。
This paper presents an enhanced multi-baseline phase unwrapping algorithm by combining an unscented Kalman filter with an enhanced joint phase gradient estimator based on the amended matrix pencil model, and an optimal path-following strategy based on phase quality estimate function. The enhanced joint phase gradient estimator can accurately and effectively extract the phase gradient information of wrapped pixels from noisy interferograms, which greatly increases the performances of the proposed method. The optimal path-following strategy ensures that the proposed algorithm simultaneously performs noise suppression and phase unwrapping along the pixels with high-reliance to the pixels with low-reliance. Accordingly, the proposed algorithm can be predicted to obtain better results, with respect to some other algorithms, as will be demonstrated by the results obtained from synthetic data.