北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2016, Vol. 39 ›› Issue (2): 10-14,34.doi: 10.13190/j.jbupt.2016.02.002

• 论文 • 上一篇    下一篇

一种新的INSAR相位解缠方法

孙学宏1,2,3, 于向明1,2, 刘丽萍1,2, 曾志民3, 张成1,2   

  1. 1. 宁夏大学 物理与电子电气工程学院, 银川 750021;
    2. 宁夏沙漠信息智能感知重点实验室, 银川 750021;
    3. 北京邮电大学 信息与通信工程学院, 北京 100876
  • 收稿日期:2015-12-14 出版日期:2016-04-28 发布日期:2016-04-28
  • 作者简介:孙学宏(1974-),男,博士生,副教授,硕士生导师,E-mail:nxsunxh@163.com.
  • 基金资助:

    宁夏自然科学基金项目(NZ14045);国家自然科学基金项目(61461044)

Phase Unwrapping Method for INSAR

SUN Xue-hong1,2,3, YU Xiang-ming1,2, LIU Li-ping1,2, ZENG Zhi-min3, ZHANG Cheng1,2   

  1. 1. School of Physics and Electronic-Electrical Engineering, Ningxia University, Yinchuan 750021, China;
    2. Ningxia Key Laboratory of Intelligent Sensing for Desert Information, Yinchuan 750021, China;
    3. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Received:2015-12-14 Online:2016-04-28 Published:2016-04-28

摘要:

针对Goldstein枝切线法存在的问题,根据残差点的分布特点,提出了一种新的干涉合成孔径雷达相位解缠方法.该方法首先对邻近偶极子对进行预处理,生成独立且长度很短的枝切线,使用自适应遗传模拟退火算法计算剩余正负残差点的优化组合,不仅在短时间内设置出总体长度较短的枝切线,且有效地避免了大面积"孤岛"出现.实验结果表明,相比于几种典型的相位解缠算法,该方法在时间和精度上具有优越性.

关键词: 干涉合成孔径雷达, 相位解缠, 枝切线, 遗传算法, 模拟退火算法

Abstract:

Due to disadvantages of Goldstein's branch cut algorithm, a new phase unwrapping method for interferometric synthetic aperture radar (INSAR) was proposed according to distribution characteristics of residue. Firstly, the neighbor dipoles preprocessing algorithm was performed to establish independent and short branch cuts. Secondly, the adaptive genetic simulated annealing algorithm was performed to calculate optimized combination of remaining residues. Ultimately, the branch cuts with short length was generated in a short time, and large "isolated island" phenomenon was avoided. Experiment shows that the proposed method has advantages in precision and operation time compared with some typical phase unwrapping algorithm.

Key words: interferometric synthetic aperture radar, phase unwrapping, branch cut, genetic algorithm, simulated annealing algorithm

中图分类号: