相位解缠的CKF局部多项式系数递推估计法

doi:10.11947/j.AGCS.2020.20190385

测绘学报 ›› 2020, Vol. 49 ›› Issue (8): 1023-1031.doi: 10.11947/j.AGCS.2020.20190385

相位解缠的CKF局部多项式系数递推估计法

谢先明, 孙玉铮, 梁小星, 曾庆宁, 郑展恒

桂林电子科技大学信息与通信学院, 广西桂林 541004

收稿日期:2019-09-18 修回日期:2020-06-04 发布日期:2020-08-25
通讯作者: 孙玉铮 E-mail:814824985@qq.com
作者简介:谢先明(1979-),男,博士生,研究员,研究方向为干涉合成孔径雷达三维信息获取。E-mail:xxmxgm@163.com
基金资助:
国家自然科学基金（41661092；61961009）；广西自然科学基金（2018GXNSFAA281196；2016GXNSFDA380018）；认知无线电与信息处理省部共建教育部重点实验室（CRK170108）；广西无线宽带通信与信号处理重点实验室基金（GXKL06180102）

Recursive estimation method of cubature Kalman filtering local polynomial coefficients for phase unwrapping

XIE Xianming, SUN Yuzheng, LIANG Xiaoxing, ZENG Qingning, ZHENG Zhanheng

School of Information and Communication Engineering, Guilin University of Electronic Technology, Guilin 541004, China

Received:2019-09-18 Revised:2020-06-04 Published:2020-08-25
Supported by:
The National Natural Science Foundation of China (NSFC) (Nos. 41661092;61961009);The Guangxi Natural Science Foundation (Nos. 2018GXNSFAA281196;2016GXNSFDA380018);The Ministry of Education Key Lab. Of Cognitive Radio and Information Processing (No. CRK170108);The Dean Project of Guangxi Key Laboratory of Wireless Broadband Communication and Signal Processing (No. GXKL06180102)

摘要/Abstract

摘要： 为从含噪干涉相位数据中估计出解缠相位，本文提出相位解缠的CKF局部多项式系数递推估计法。利用基于修正矩阵束模型的局部相位梯度估计算法（AMPM）来获取多项式系数中的梯度信息，在此基础上获得局部多项式系数初始值（即状态变量初值），最后利用容积卡尔曼滤波（CKF）算法递推估计多项式系数状态估计值，从而获得解缠相位。可根据干涉图条纹密度以及相位噪声情况，分别采用逐行（或逐列）扫描方式或质量图引导策略引导容积卡尔曼滤波器解缠干涉图缠绕像元。模拟样例与实测数据试验结果表明，与其他同类方法相比，本文算法能从噪声干涉图中获得更高的解缠精度。

关键词: 相位解缠, 局部多项式近似, 容积卡尔曼滤波, 梯度估计

Abstract: Recursive estimation method of cubature kalman filtering(CKF) local polynomial coefficients for phase unwrapping is proposed to retrieve unambiguous unwrapping phase from noisy wrapped phase. First, phase gradient information required is obtained using amended matrix pencil model (AMPM), and then the initial state estimation value of the polynomial coefficients is obtained. Finally, the polynomial coefficients are recursively estimated to obtain the unambiguous unwrapping phase by using the cubature Kalman filter. According to the density of the fringes of the interferograms and the signal-to-noise ratio (SNR) of the interferograms, the row-by-row (or column-by-column) scanning modes or the quality-guide strategy applied in traditional algorithms can be used to guide the cubature Kalman filter to unwrap the wrapped pixels along the suitable paths. The results with the simulated data and the measured data demonstrate that the algorithm in this paper can obtain robust solutions from noisy interferograms, with respect to some other similar algorithms.

Key words: phase unwrapping, local polynomial approximation, cubature Kalman filter, gradient estimate

中图分类号:

P236

谢先明, 孙玉铮, 梁小星, 曾庆宁, 郑展恒. 相位解缠的CKF局部多项式系数递推估计法[J]. 测绘学报, 2020, 49(8): 1023-1031.

XIE Xianming, SUN Yuzheng, LIANG Xiaoxing, ZENG Qingning, ZHENG Zhanheng. Recursive estimation method of cubature Kalman filtering local polynomial coefficients for phase unwrapping[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(8): 1023-1031.

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相位解缠的CKF局部多项式系数递推估计法

Recursive estimation method of cubature Kalman filtering local polynomial coefficients for phase unwrapping

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