一种基于似然比统计量的SAR相干变化检测

赵军香; 梁兴东; 李焱磊

doi:10.12000/JR16065

一种基于似然比统计量的SAR相干变化检测

doi: 10.12000/JR16065

赵军香^①,②, ,,
梁兴东^①,,
李焱磊^①,

①.
中国科学院电子学研究所微波成像技术国家级重点实验室北京 100190
②.
中国科学院大学北京 100049

基金项目:

国家863计划船载无人机海洋观测系统 2013AA092105

国家863计划船载无人机海洋观测系统 201412002

详细信息

作者简介:
赵军香 (1989–), 女, 中国科学院电子学研究所硕士研究生, 研究方向为雷达信号处理。E-mail:jxzhao_0817@163.com

梁兴东 (1973–), 男, 中国科学院电子学研究所研究员, 研究领域包括高分辨率合成孔径雷达系统、干涉合成孔径雷达系统、成像处理及应用和实时数字信号处理。E-mail:xdliang@mail.ie.ac.cn

李焱磊 (1983–), 男, 中国科学院电子学研究所助理研究员, 研究方向为机载差分干涉SAR信号处理。E-mail:yllee@mail.ie.ac.cn

通讯作者:
赵军香, E-mail:jxzhao_0817@163.com

中图分类号: TN957.51
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出版历程
- 收稿日期: 2016-03-28
- 修回日期: 2016-06-15
- 网络出版日期: 2017-04-28

Change Detection in SAR CCD Based on the Likelihood Change Statistics

Zhao Junxiang^{①,②
, ,},
Liang Xingdong^{①
,},
Li Yanlei^{①
,}

①.
National Key Laboratory of Science and Technology on Microwave Imaging, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China)
②.
University of Chinese Academy of Sciences, Beijing 100049, China)

Funds:

National 863 Plan Ship-carried UAV Ocean Observation System 2013AA092105

Surveying and Mapping Geographic Information Public Service Industry Research Projects 201412002

摘要

摘要: 相干变化检测利用相位差异可以检测出场景中的微小变化。该文针对相干变化检测中的两个问题：虚警高和阈值难选择，在原有似然比检测算法的基础上做了两点改进：运用最大似然估计优化似然比统计量中的参数，并采用邻域滑动窗口使得参数估计结果更加准确稳健；根据差异图像直方图提出了一种基于邻域直方图差的自动阈值选取方法。实测数据处理结果验证了算法的有效性。
- 合成孔径雷达 /
- 相干变化检测 /
- 似然比 /
- 自动阈值
Abstract: The Coherent Change Detection (CCD) measures the phase difference in repeat passes in SAR images and is a powerful technique for detecting minute changes between two synthetic aperture radar images taken at different times. Nevertheless, the CCD has two problems. These are the high false-alarm rates and threshold selection. To deal with these problems using the likelihood change, this study makes two improvements. First, the model parameters are optimized by the maximum likelihood method and more accurate and robust parameters are obtained by using the sliding window in the neighborhood operations. Second, the automatic change in the threshold method is proposed based on the histogram characteristics of different data. The processing of real data suggests that the proposed method is effective in detecting minute changes.
- Synthetic Aperture Radar (SAR) /
- Coherent Change Detection (CCD) /
- Likelihood ratio /
- Automatic threshold

HTML全文

图 1 ROC曲线

Figure 1. ROC curves

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图 2 窗口的选择

Figure 2. Two different windows

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图 3 基于似然比变化检测的流程图

Figure 3. A change detection based on the likelihood change statistic for SAR CCD

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图 4 理想中差异图像的直方图

Figure 4. Ideal histogram of likelihood change statistic

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图 5 实测数据得到的差异影像直方图

Figure 5. Histogram of likelihood change statistic

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图 6 自动阈值选取方法

Figure 6. The results of automatic threshold selection

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图 7 地面真实变化

Figure 7. Ground truth observations of the changed scene

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图 8 估计全局协方差矩阵的样本

Figure 8. The sample data for estimation of the covariance matrixes

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图 9 检测结果

Figure 9. Detection results

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图 10 三种算法的ROC曲线

Figure 10. Experimental ROC curves of the three change detection method

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表 1 LLR_CCD方法和CCD方法的性能指标

Table 1. Results of change detection by CCD and LLR_CCD

性能评估参数	LLR_CCD			CCD
性能评估参数	本文阈值选取方法	OSTU	手动最佳阈值	本文阈值选取方法	OSTU	手动最佳阈值
阈值	–104.83	72.06	–125	0.77	0.71	0.32
检测率P_TP	0.7281	1	0.6641	1	0.9984	0.5703
负检率P_TN	0.9965	0.3811	0.9989	0.8737	0.9134	0.9933
虚警率P_FP	0.0035	0.6189	0.0011	0.1263	0.0866	0.0067
漏检率P_FN	0.2719	0	0.3359	0	0.0016	0.4297
Kappa	0.7454	0.0193	0.7626	0.1811	0.2517	0.5684

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