• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2015, Vol. 37 ›› Issue (03): 611-615.

• 论文 • 上一篇    下一篇

基于随机并行梯度下降算法的InSAR相位解缠方法

杨新锋1,宋长斌2,刘克成1   

  1. (1.南阳理工学院计算机与信息工程学院,河南 南阳 473004;2.南阳广播电视大学,河南 南阳 473004)
  • 收稿日期:2013-10-17 修回日期:2014-02-19 出版日期:2015-03-25 发布日期:2015-03-25
  • 基金资助:

    国家自然科学基金资助项目(60873120);河南省科技攻关资助项目(122102210563)

Phase unwrapping for InSAR based on
stochastic parallel gradient descent algorithm  

YANG Xinfeng1,SONG Changbin2,LIU Kecheng1   

  1. (1.School of Computer and Information Engineering,Nanyang Institute of Technology,Nanyang 473004;
    2.Nanyang Radio and TV University,Nanyang 473004,China)
  • Received:2013-10-17 Revised:2014-02-19 Online:2015-03-25 Published:2015-03-25

摘要:

相位解缠是干涉合成孔径雷达InSAR数据处理中的一个关键步骤,解缠结果的好坏直接影响最终数字高程模型的精度。介绍了一种基于随机并行梯度下降SPGD算法的解缠方法,该方法对图像中各相位点施加随机并行扰动,通过迭代使得解缠误差代价函数收敛到全局最优值,从而实现相位解缠的目的。模拟和实测数据实验结果表明,相较于最小二乘解缠方法,随机并行梯度下降解缠算法精度更高,且原理简单,易于实现,为相位解缠提供了一个全新的思路。

关键词: 相位解缠, 干涉合成孔径雷达, 随机并行梯度下降, 最小二乘

Abstract:

Phase unwrapping is one of the key data processing procedures for interferometric Synthetic Aperture Radar (InSAR), which can directly affect the final precision of the digital elevation model. A phase unwrapping method based on Stochastic Parallel Gradient Descent (SGPD) algorithm is proposed in the paper, which imposes the stochastic parallel perturbation on every point of the phase images and achieves the phase unwrapping through iteration by which the error cost function is converged to its global extremum. Experimental results of simulated and real data indicate that the SPGDbased phase unwrapping method is more precise, simple and easy to realize, and provides a total new solution to phase unwrapping.

Key words: phase unwrapping;interferometric synthetic aperture radar;stochastic parallel gradient descent;least square