高级搜索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于粗数字高程模型信息的干涉相位图生成方法

郭交 李真芳 刘艳阳 保铮

郭交, 李真芳, 刘艳阳, 保铮. 基于粗数字高程模型信息的干涉相位图生成方法[J]. 电子与信息学报, 2010, 32(11): 2642-2647. doi: 10.3724/SP.J.1146.2010.00345
引用本文: 郭交, 李真芳, 刘艳阳, 保铮. 基于粗数字高程模型信息的干涉相位图生成方法[J]. 电子与信息学报, 2010, 32(11): 2642-2647. doi: 10.3724/SP.J.1146.2010.00345
Guo Jiao, Li Zhen-Fang, Liu Yan-Yang, Bao Zheng. Approaches to Interferogram Generation Based on Coarse DEM[J]. Journal of Electronics & Information Technology, 2010, 32(11): 2642-2647. doi: 10.3724/SP.J.1146.2010.00345
Citation: Guo Jiao, Li Zhen-Fang, Liu Yan-Yang, Bao Zheng. Approaches to Interferogram Generation Based on Coarse DEM[J]. Journal of Electronics & Information Technology, 2010, 32(11): 2642-2647. doi: 10.3724/SP.J.1146.2010.00345

基于粗数字高程模型信息的干涉相位图生成方法

doi: 10.3724/SP.J.1146.2010.00345
基金项目: 

国家自然科学基金(60802074)和教育部新世纪优秀人才支持计划联合资助课题

Approaches to Interferogram Generation Based on Coarse DEM

  • 摘要: 该文提出了一种基于粗数字高程模型(DEM)信息的干涉相位图生成方法,其思路为充分利用已有的DEM信息来完成SAR图像配准-干涉相位滤波处理。此方法首先根据粗DEM信息和系统参数计算得到SAR图像中每一像素的2维配准偏移量,从而完成SAR图像的配准。在干涉相位滤波中,由粗DEM信息仿真生成已知地形的干涉条纹图用以补偿InSAR系统录取得到的干涉相位,再对残余相位进行滤波处理,提高干涉相位滤波的性能。另外,对于高分辨率SAR图像,粗DEM高程误差和系统参数误差会引入较大的图像配准误差,该文再利用联合像素子空间投影方法进一步完成SAR图像的精确配准和相位滤波。仿真结果验证了该文方法的有效性。
  • Rosen P A, Hensley S, and Joughin I R, et al.. Synthetic aperture radar interferometry[J].Proceedings of IEEE.2000, 88(3):333-382[2]Peterson E H, Fotopoulos G, and Zee R E. A feasibility assessment for low-cost InSAR formation-flying microsatellites[J].IEEE Transactions on Geoscience Remote Sensing.2009, 47(8):2847-2858[3]彭石宝,袁俊泉,向家彬. 一种基于加权迭代贪婪算法的InSAR相位解缠新方法[J].电子与信息学报.2008, 30(6):1326-1330浏览Peng Shi-bao, Yuan Jun-quan, and Xiang Jia-bin. An improved InSAR phase unwrapping method based on interative-weighted greedy algorithm[J].Journal of Electronics Information Technology.2008, 30(6):1326-1330[4]Ferraluolo G, Meglio F, and Pascazio V, et al.. DEM reconstruction accuracy in multichannel SAR interferometry[J].IEEE Transactions on Geoscience Remote Sensing.2009, 47(1):191-201[5]Meng D, Sethu V, and Ambikairajah E, et al.. A novel technique for noise reduction in InSAR images[J].IEEE Geoscience and Remote Sensing Letters.2007, 4(2):226-230[6]Guarnieri A M and Tebaldini S. ML-based fringe-frequency estimation for InSAR[J].IEEE Geoscience and Remote Sensing Letters.2010, 7(1):136-140[7]Li Hai, Li Zhen-fang, and Liao Gui-sheng, et al.. An estimation method for InSAR interferometric phase combined with image auto-coregistration[J].Science in China, Series F.2006, 49(3):386-396[8]Li Zhen-fang, Bao Zheng, and Li Hai, et al.. Image auto-coregistration and InSAR interferogram estimation using joint subspace projection[J].IEEE Transactions on Geoscience Remote Sensing.2006, 44(2):288-297[9]Xu Hua-ping and Kang Chang-hui. Equivalence analysis of accuracy of geolocation models for spaceborne InSAR[J].IEEE Transactions on Geoscience Remote Sensing.2010, 48(1):480-490[10]Krieger G, Moreira A, and Fiedler H. TanDEM-X: A satellite formation for high-resolution SAR interferometry[J].IEEE Transactions on Geoscience Remote Sensing.2007, 45(11):3317-3341[11]Gonzalez J H, Bachmann M, and Krieger G. Development of the TanDEM-X calibration concept: Analysis of systematic errors[J].IEEE Transactions on Geoscience Remote Sensing.2010, 48(2):716-726
  • 加载中
计量
  • 文章访问数:  4180
  • HTML全文浏览量:  105
  • PDF下载量:  702
  • 被引次数: 0
出版历程
  • 收稿日期:  2010-04-06
  • 修回日期:  2010-06-18
  • 刊出日期:  2010-11-19

目录

    /

    返回文章
    返回