Multi-band SAR Coherent Change Detection Method Based on Coherent Representation Differences of Targets

Ji Guangyu; Dong Yongwei; Bu Yuncheng; Li Yanlei; Zhou Liangjiang; Liang Xingdong

doi:10.12000/JR18020

Volume 7 Issue 4

Aug. 2018

Turn off MathJax

Article Contents

Abstract

References

Article Navigation > Journal of Radars > 2018 > 7(4): 455-464

Ji Guangyu, Dong Yongwei, Bu Yuncheng, Li Yanlei, Zhou Liangjiang, Liang Xingdong. Multi-band SAR Coherent Change Detection Method Based on Coherent Representation Differences of Targets[J]. Journal of Radars, 2018, 7(4): 455-464. doi: 10.12000/JR18020

Citation:

Ji Guangyu, Dong Yongwei, Bu Yuncheng, Li Yanlei, Zhou Liangjiang, Liang Xingdong. Multi-band SAR Coherent Change Detection Method Based on Coherent Representation Differences of Targets[J]. Journal of Radars, 2018, 7(4): 455-464. doi: 10.12000/JR18020

Citation:

Ji Guangyu, Dong Yongwei, Bu Yuncheng, Li Yanlei, Zhou Liangjiang, Liang Xingdong. Multi-band SAR Coherent Change Detection Method Based on Coherent Representation Differences of Targets[J]. Journal of Radars, 2018, 7(4): 455-464. doi: 10.12000/JR18020

PDF( 2005 KB)

Multi-band SAR Coherent Change Detection Method Based on Coherent Representation Differences of Targets

DOI: 10.12000/JR18020

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

Funds: The National Ministries Foundation

Received Date: 2018-03-07
Rev Recd Date: 2018-03-14
Publish Date: 2018-08-28

Abstract

Abstract

Coherent Change Detection (CCD) detects micro changes in a scene using phase coherence of SAR images before and after a change. It is difficult for conventional CCD method to distinguish low coherence interference region from objective change region because of a single detection scale. Multi-band SAR target detection in a multiscale way develops variable coherent representation according to the diversity of electromagnetic wave penetration, target structure, and change magnitude. In this paper, a multi-band CCD method is proposed. Firstly, the CCD images of every band were acquired; secondly, the detected scene was classified on the basis of coherent representation of targets in each single band using improved Expectation-Maximization (EM) algorithm; thirdly, the objective change class in each single band was selected by a few supervised samples; lastly, multi-band fusion CCD image was acquired by the use of Dempster-Shafer (DS) evidence theory. This multi-band CCD result can eliminate low coherent interference in each single band and decrease false alarm probability. The method is validated by L- and P-band repeat-pass SAR images acquired before and after change. Results and index parameters demonstrate the validity and correctness of the proposed method.

FullText(HTML)

References(25)

References

[1]	Preiss M and Stacy N J S. Coherent change detection: Theoretical description and experimental results[R]. DSTO-TR-1851, 2006
[2]	Jung J, Kim D J, Lavalle M, et al. Coherent change detection using InSAR temporal decorrelation model: A case study for volcanic ash detection[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(10): 5765–5775. DOI: 10.1109/TGRS.2016.2572166
[3]	Barber J and Kogon S. Probabilistic three-pass SAR coherent change detection[C]. Proceedings of 2012 Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), Pacific Grove, California, USA, 2012: 1723–1726. DOI: 10.1109/ACSSC.2012.6489327
[4]	Muhuri A, Ratha D, and Bhattacharya A. Seasonal snow cover change detection over the Indian Himalayas using polarimetric SAR images[J]. IEEE Geoscience and Remote Sensing Letters, 2017, 14(12): 2340–2344. DOI: 10.1109/LGRS.2017.2764123
[5]	Wahl D E, Yocky D A, Jakowatz C V, et al. A new maximum-likelihood change estimator for two-pass SAR coherent change detection[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(4): 2460–2469. DOI: 10.1109/TGRS.2015.2502219
[6]	冷英, 李宁. 一种改进的变化检测方法及其在洪水监测中的应用[J]. 雷达学报, 2017, 6(2): 204–212. DOI: 10.12000/JR16139 Leng Ying and Li Ning. Improved change detection method for flood monitoring[J]. Journal of radars, 2017, 6(2): 204–212. DOI: 10.12000/JR16139
[7]	An L, Li M, Zhang P, et al. Discriminative random fields based on maximum entropy principle for semisupervised SAR image change detection[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016, 9(8): 3395–3404. DOI: 10.1109/JSTARS.2015.2483320
[8]	徐真, 王宇, 李宁, 等. 一种基于CNN的SAR图像变化检测方法[J]. 雷达学报, 2017, 6(5): 483–491. DOI: 10.12000/JR17075 Xu Zhen, Wang Robert, Li Ning et al. A novel approach to change detection in SAR images with CNN classification[J]. Journal of radars, 2017, 6(5): 483–491. DOI: 10.12000/JR17075
[9]	Nielsen A A, Conradsen K, and Skriver H. Change detection in full and dual polarization, single-and multifrequency SAR data[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015, 8(8): 4041–4048. DOI: 10.1109/JSTARS.2015.2416434
[10]	Nielsen A A, Conradsen K, and Skriver H. Corrections to " change detection in full and dual polarization, single-and multi-frequency SAR data”[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017, 10(11): 5143–5144. DOI: 10.1109/JSTARS.2017.2761038
[11]	Reigber A, Jäger M, and Krogager E. Polarimetric SAR change detection in multiple frequency bands for environmental monitoring in Arctic regions[C]. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China, 2016: 5702–5705. DOI: 10.1109/IGARSS.2016.7730489
[12]	Li Y L, Liang X D, Zhou L J, et al.. Introduction to IECAS-SAR — A multi-frequency polarimetric airborne SAR[C]. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Quebec City, Quebec, Canada, 2014: 1085–1088. DOI: 10.1109/IGARSS.2014.6946617
[13]	Jackson J A and Moses R L. Feature extraction algorithm for 3D scene modeling and visualization using monostatic SAR[C]. Proceedings of SPIE 6237 Algorithms for Synthetic Aperture Radar Imagery XIII, Orlando, 2006, 6237: 623708. DOI: 10.1117/12.666558
[14]	文贡坚, 朱国强, 殷红成, 等. 基于三维电磁散射参数化模型的SAR目标识别方法[J]. 雷达学报, 2017, 6(2): 115–135. DOI: 10.12000/JR17034 Wen Gongjian, Zhu Guoqiang, Yin Hongcheng, et al. SAR ATR based on 3D parametric electromagnetic scattering model[J]. Journal of radars, 2017, 6(2): 115–135. DOI: 10.12000/JR17034
[15]	袁孝康. 星载合成孔径雷达导论[M]. 北京: 国防工业出版社, 2003: 234–235 Yuan Xiao-kang. Introduce to the Spaceborne Sythetic Aperture Radar[M]. Beijing: National Defense Industry Press, 2003: 234–235
[16]	陈述彭, 童庆禧, 郭华东. 遥感信息机理研究[M]. 北京: 科学出版社, 1998: 274–288 Chen Shu-peng, Tong Qing-xi, and Guo Hua-dong. Mechanism of Remote Sensing Information[M]. Beijing: Science Press, 1998: 274–288
[17]	周智敏, 黄晓涛. VHF/UHF超宽带合成孔径雷达穿透性能分析[J]. 系统工程与电子技术, 2003, 25(11): 1336–1340. DOI: 10.3321/j.issn:1001-506X.2003.11.007 Zhou Zhi-min and Huang Xiao-tao. Penetration performance analysis of VHF/UHF ultra-wideband synthetic aperture radar[J]. Systems Engineering and Electronics, 2003, 25(11): 1336–1340. DOI: 10.3321/j.issn:1001-506X.2003.11.007
[18]	Yin Q, Li Y, Huang P P, et al. Analysis of InSAR coherence loss caused by soil moisture variation[J]. Journal of Radars, 2015, 4(6): 689–697. DOI: 10.12000/JR15075
[19]	黄培康, 殷红成, 许小剑. 雷达目标特性[M]. 北京: 电子工业出版社, 2005: 9–62 Huang Pei-kang, Yin Hong-cheng, and Xu Xiao-jian. Radar Target Characteristics[M]. Beijing: Publishing House of Electronics Industry, 2005: 9–62
[20]	冀广宇, 董勇伟, 李焱磊, 等. 一种基于概率图模型的多时相SAR相干变化检测方法[J]. 电子与信息学报, 2017, 39(12): 2912–2920. DOI: 10.11999/JEIT170208 Ji Guang-yu, Dong Yong-wei, Li Yan-lei, et al. A multi-temporal SAR coherent change detection method based on probabilistic graphical models[J]. Journal of Electronics&Information Technology, 2017, 39(12): 2912–2920. DOI: 10.11999/JEIT170208
[21]	尤红建, 付琨. 合成孔径雷达图像精准处理[M]. 北京: 科学出版社, 2011: 125–139 You Hong-jian and Fu Kun. Precise Processing of Synthetic Aperture Radar Images[M]. Beijing: Science Press, 2011: 125–139
[22]	Touzi R, Lopes A, Bruniquel J, et al. Coherence estimation for SAR imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(1): 135–149. DOI: 10.1109/36.739146
[23]	Anfinsen S N and Eltoft T. Application of the matrix-variate mellin transform to analysis of polarimetric radar images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(6): 2281–2295. DOI: 10.1109/TGRS.2010.2103945
[24]	杨祥立, 徐德伟, 黄平平, 等. 融合相干/非相干信息的高分辨率SAR图像变化检测[J]. 雷达学报, 2015, 4(5): 582–590. DOI: 10.12000/JR15073 Yang Xiang-li, Xu De-wei, Huang Ping-ping, et al. Change detection of high resolution SAR images by the fusion of coherent/incoherent information[J]. Journal of Radars, 2015, 4(5): 582–590. DOI: 10.12000/JR15073
[25]	王桂婷, 王幼亮, 焦李成. 基于快速EM算法和模糊融合的多波段遥感影像变化检测[J]. 红外与毫米波学报, 2010, 29(5): 383–388 Wang Gui-ting, Wang You-liang, and Jiao Li-cheng. Change detection method of multiband remote sensing images based on fast expectation-maximization algorithm and fuzzy fusion[J]. Journal of Infrared and Millimeter Waves, 2010, 29(5): 383–388

Relative Articles

[1]	XING Mengdao, MA Penghui, LOU Yishan, SUN Guangcai, LIN Hao. Review of Fast Back Projection Algorithms in Synthetic Aperture Radar[J]. Journal of Radars, 2024, 13(1): 1-22. doi: 10.12000/JR23183
[2]	HUANG Pingping, DUAN Yinghong, TAN Weixian, XU Wei. Change Detection Method Based on Fusion Difference Map in Flood Disaster[J]. Journal of Radars, 2021, 10(1): 143-158. doi: 10.12000/JR20118
[3]	HUANG Pingping, REN Huifang, TAN Weixian, DUAN Yinghong, XU Wei, LIU Fang. Unsupervised Change Detection Using Ground-based Radar Image[J]. Journal of Radars, 2020, 9(3): 514-524. doi: 10.12000/JR20004
[4]	WANG Yuqi, SUN Guangcai, YANG Jun, XING Mengdao, YANG Xiaoniu, BAO Zheng. Passive Localization Algorithm for Radiation Source Based on Long Synthetic Aperture[J]. Journal of Radars, 2020, 9(1): 185-194. doi: 10.12000/JR19080
[5]	XING Mengdao, LIN Hao, CHEN Jianlai, SUN Guangcai, YAN Bangbang. A Review of Imaging Algorithms in Multi-platform-borne Synthetic Aperture Radar[J]. Journal of Radars, 2019, 8(6): 732-757. doi: 10.12000/JR19102
[6]	Xu Zhen, Wang Robert, Li Ning, Zhang Heng, Zhang Lei. A Novel Approach to Change Detection in SAR Images with CNN Classification[J]. Journal of Radars, 2017, 6(5): 483-491. doi: 10.12000/JR17075
[7]	Leng Ying, Li Ning. Improved Change Detection Method for Flood Monitoring[J]. Journal of Radars, 2017, 6(2): 204-212. doi: 10.12000/JR16139
[8]	Zhao Junxiang, Liang Xingdong, Li Yanlei. Change Detection in SAR CCD Based on the Likelihood Change Statistics[J]. Journal of Radars, 2017, 6(2): 186-194. doi: 10.12000/JR16065
[9]	Zhao Yongsheng, Zhao Yongjun, Zhao Chuang. Weighted Least Squares Algorithm for Single-observer Passive Coherent Location Using DOA and TDOA Measurements[J]. Journal of Radars, 2016, 5(3): 302-311. doi: 10.12000/JR15133
[10]	Li Lei, Li Guo-lin, Liu Run-jie. Novel Direction Of Arrival Estimation Method Based on Coherent Accumulation Matrix Reconstruction[J]. Journal of Radars, 2015, 4(2): 178-184. doi: 10.12000/JR14116
[11]	Guo Xiao-yang, Li Yang, Lin Yun, Guo Sheng-long, Hong Wen. Statistical Models of Speckle for Circular SAR Imaging[J]. Journal of Radars, 2015, 4(6): 708-714. doi: 10.12000/JR15039
[12]	Yang Xiang-li, Xu De-wei, Huang Ping-ping, Yang Wen. Change Detection of High Resolution SAR Images by the Fusion of Coherent/Incoherent Information[J]. Journal of Radars, 2015, 4(5): 582-590. doi: 10.12000/JR15073
[13]	Yin Qiang, Li Yang, Huang Ping-ping, Lin Yun, Hong Wen. Analysis of InSAR Coherence Loss Caused by Soil Moisture Variation(in English)[J]. Journal of Radars, 2015, 4(6): 689-697. doi: 10.12000/JR15075
[14]	Wang Shuang, Yu Jia-ping, Liu Kun, Hou Biao, Jiao Li-cheng. Polarimetric SAR Speckle Reduction Based on Bilateral Filtering[J]. Journal of Radars, 2014, 3(1): 35-44. doi: 10.3724/SP.J.1300.2014.13133
[15]	Li Hai-ying, Zhang Shan-shan, Li Shi-qiang, Zhang Hua-chun. Coherent Performance Analysis of the HJ-1-C Synthetic Aperture Radar[J]. Journal of Radars, 2014, 3(3): 320-325. doi: 10.3724/SP.J.1300.2014.13060
[16]	Zhang Wen-bin, Deng Yun-kai, Wang Yu. A Fast Back Projection Algorithm for Spotlight Mode Bi-SAR Imaging[J]. Journal of Radars, 2013, 2(3): 357-366. doi: 10.3724/SP.J.1300.2013.13031
[17]	Li Guang-ting, Huang Ping-ping, Yu Wei-dong. Non-Local SAR Image Despeckling Based on Similar Pixels Selected[J]. Journal of Radars, 2012, 1(2): 171-181. doi: 10.3724/SP.J.1300.2012.20034
[18]	Li Guang-ting, Yang Liang, Huang Ping-ping, Yu Wei-dong. The Pixel-similarity Measurement in SAR Image Despeckling[J]. Journal of Radars, 2012, 1(3): 301-308. doi: 10.3724/SP.J.1300.2012.20025
[19]	Zheng Jin, You Hong-jian. Change Detection with SAR Images Based on Radon Transform and Jeffrey Divergence[J]. Journal of Radars, 2012, 1(2): 182-189. doi: 10.3724/SP.J.1300.2012.10068
[20]	Llin Shi-bin, Li Yue-li, Yan Shao-shi, Zhou Zhi-min. Study of Effects of Flat Surface Assumption to Synthetic Aperture Radar Time-domain Algorithms Imaging Quality[J]. Journal of Radars, 2012, 1(3): 309-313. doi: 10.3724/SP.J.1300.2012.20035

Supplements(0)

Cited By

Cited by

Periodical cited type(2)

1.	王源，陈富龙，胡祺，唐攀攀. COSMO-SkyMed时序影像南京城市变化检测研究. 遥感技术与应用. 2019(05): 1054-1063 .
2.	王志浩，张金松，孙光才，李军，邢孟道. 一种联合多特征量的SAR人造微弱痕迹检测方法. 西安电子科技大学学报. 2019(06): 131-139 .

Other cited types(3)

Proportional views

Proportional views

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

Get Citation

PDF

XML

Article views(3476) PDF downloads(434)