极化串扰对基于Cloude分解的地物散射机制特征量影响分析

胡丁晟 仇晓兰 雷斌 徐丰

胡丁晟, 仇晓兰, 雷斌, 徐丰. 极化串扰对基于Cloude分解的地物散射机制特征量影响分析[J]. 雷达学报, 2017, 6(2): 221-228. doi: 10.12000/JR16129
引用本文: 胡丁晟, 仇晓兰, 雷斌, 徐丰. 极化串扰对基于Cloude分解的地物散射机制特征量影响分析[J]. 雷达学报, 2017, 6(2): 221-228. doi: 10.12000/JR16129
Hu Dingsheng, Qiu Xiaolan, Lei Bin, Xu Feng. Analysis of Crosstalk Impact on the Cloude-decomposition-based Scattering Characteristic[J]. Journal of Radars, 2017, 6(2): 221-228. doi: 10.12000/JR16129
Citation: Hu Dingsheng, Qiu Xiaolan, Lei Bin, Xu Feng. Analysis of Crosstalk Impact on the Cloude-decomposition-based Scattering Characteristic[J]. Journal of Radars, 2017, 6(2): 221-228. doi: 10.12000/JR16129

极化串扰对基于Cloude分解的地物散射机制特征量影响分析

doi: 10.12000/JR16129
基金项目: 国家自然科学基金(61331017),高分三号卫星应用共性关键技术项目(30-Y20A12-9004-15/16, 03-Y20A11-9001-15/16)
详细信息
    作者简介:

    胡丁晟(1989–),男,浙江金华人,博士生,研究方向为极化SAR统计建模、定标处理技术。E-mail: hds_iecas@hotmail.com

    仇晓兰(1982–),女,江苏苏州人,中国科学院电子学研究所副研究员,研究方向为SAR成像技术、双基地SAR技术。E-mail: xlqiu@mail.ie.ac.cn

    雷斌:雷   斌(1978–),男,研究员,研究方向为多传感器遥感信息处理系统体系架构设计、SAR信号并行处理、SAR图像处理与图像质量提升和SAR系统性能预估与优化等。E-mail: leibin@mail.ie.ac.cn

    徐丰:徐   丰(1980–),男,民政部国家减灾中心副研究员,研究方向为SAR图像分类、目标识别及其应用。

    通讯作者:

    仇晓兰   xlqiu@mail.ie.ac.cn

  • 中图分类号: TN957.52

Analysis of Crosstalk Impact on the Cloude-decomposition-based Scattering Characteristic

Funds: The National Natural Science Foundation of China (61331017), The GF-3 High-Resolution Earth Observation System under Project (30-Y20A12-9004-15/16, 03-Y20A11-9001-15/16)
  • 摘要: 串扰是极化SAR系统的主要误差源之一,也是用于衡量极化定标质量的参考指标。为研究系统串扰在具体地物分类应用中的影响,该文首先推导了串扰量作用于由Cloude分解获得的地物散射机制特征量的数学表达,并利用不同类型的实际Radarsat-2数据通过半物理仿真,验证理论分析结果。最后在实验数据上进行基于Cloude分解的H/a/Wishart非监督分类,从各类图像分类偏差比率随串扰的变化曲线中,获得满足应用需求的串扰量指标。

     

  • 图  1  H- $\alpha $平面及8类不同散射特性划分

    Figure  1.  H- $\alpha $ plane with eight divisions based on scattering characteristic

    图  2  各场景数据的Pauli分解伪彩合成图

    Figure  2.  The Pauli decomposition maps for all datasets

    图  3  不同串扰下的中心散射机制在H-$\alpha $平面上变化,红色代表城区图像,黄色代表农田图像,蓝色代表入海口图像,绿色代表丛林图像

    Figure  3.  The changing of scattering center on the H-$\alpha $ plane under different crosstalk, red represents the urban area, yellow represents the agricultural field, blue represents the estuary scene, and green represents the forest area

    图  4  不同串扰下的 $H/\alpha /{\rm{Wishart}}$分类结果

    Figure  4.  The $H/\alpha /{\rm{Wishart}}$ classification results under different crosstalk

    图  5  不同串扰下的 $H/\alpha /{\rm{Wishart}}$分类结果偏差比例变化曲线,红色代表城区图像,黄色代表农田图像,蓝色代表入海口图像,绿色代表丛林图像,黑色虚线表示分类偏差率5%指标

    Figure  5.  The bias of $H/\alpha /{\rm{Wishart}}$ classification results under different crosstalk, red represents the urban area, yellow represents the agricultural field, blue represents the estuary scene, and green represents the forest area, the black dashed line denotes the bias less than 5%

    表  1  数据情况说明

    Table  1.   The description of datasets

    图像编号 尺寸(像素) 距离向分辨率(m) 方位向分辨率(m) 中心视角(°) 场景
    1 512×512 4.76655 4.73308 34.2372 城区
    2 512×512 5.46646 4.73308 37.1864 农田
    3 512×512 4.81696 4.73308 35.2785 入海口
    4 512×512 4.81687 4.73308 35.2859 丛林
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出版历程
  • 收稿日期:  2016-11-23
  • 修回日期:  2017-02-27
  • 网络出版日期:  2017-04-28

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