Polarimetric SAR Target Scattering Interpretation in Rotation Domain: Theory and Application

Chen Siwei; Li Yongzhen; Wang Xuesong; Xiao Shunping

doi:10.12000/JR17033

Volume 6 Issue 5

Oct. 2017

Turn off MathJax

Article Contents

Abstract

References

Article Navigation > Journal of Radars > 2017 > 6(5): 442-455

DING Zihang, XIE Junwei, and WANG Bo. Missing covariance matrix recovery with the FDA-MIMO radar using deep learning method[J]. Journal of Radars, 2023, 12(5): 1112–1124. doi: 10.12000/JR23002

Citation:

Chen Siwei, Li Yongzhen, Wang Xuesong, Xiao Shunping. Polarimetric SAR Target Scattering Interpretation in Rotation Domain: Theory and Application[J]. Journal of Radars, 2017, 6(5): 442-455. doi: 10.12000/JR17033

DING Zihang, XIE Junwei, and WANG Bo. Missing covariance matrix recovery with the FDA-MIMO radar using deep learning method[J]. Journal of Radars, 2023, 12(5): 1112–1124. doi: 10.12000/JR23002

Citation:

PDF( 2003 KB)

Polarimetric SAR Target Scattering Interpretation in Rotation Domain: Theory and Application

DOI: 10.12000/JR17033

The State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, School of Electronics Science and Engineering, National University of Defense Technology, Changsha 410073, China

Funds: The National Natural Science Foundation of China (41301490, 61490690, 61490692)

Received Date: 2017-03-28
Rev Recd Date: 2017-06-28

Available Online: 2017-07-31

Publish Date: 2017-10-28

Abstract

Abstract

Backscattering of radar targets is sensitive to the relative geometry between target orientations and the radar line of sight. This scattering diversity makes imaging radar represented by polarimetric Synthetic Aperture Radar (SAR) information processing and applications very difficult. This situation has become one of the main bottlenecks in the interpretation of the target scattering mechanism and quantitative applications. In this work, we review and introduce a new interpretation of the target scattering mechanism in the rotation domain along the radar line of sight. This concept includes the recently established uniform polarimetric matrix rotation theory and polarimetric coherence pattern visualization and interpretation in the rotation domain. The core idea of target scattering interpretation in the rotation domain is to extend the amount of target information acquired at a given geometry to the rotation domain, which then provides fundamentals for the deep mining and utilization of target scattering information. This work mainly focuses on the investigation of derived new polarimetric feature sets and application demonstrations. Comparison study results validate the promising potential for the application of the established interpretation framework in the rotation domain with respect to target discrimination and classification.
- Polarimetric Synthetic Aperture Radar (PolSAR),
- Scattering mechanism,
- Rotation domain,
- Polarimetric target decomposition,
- Image interpretation

FullText(HTML)

References(49)

References

[1]	Lee J S and Pottier E. Polarimetric Radar Imaging: From Basics to Applications[M]. Boca Raton: CRC Press, 2009.
[2]	Cloude S R. Polarisation Application in Remote Sensing[M]. Oxford: Oxford University Press, 2009.
[3]	金亚秋, 徐丰. 极化散射与SAR遥感信息理论与方法[M]. 北京: 科学出版社, 2008. Jin Ya-qiu and Xu Feng. Theory and Approach for Polarimetric Scattering and Information Retrieval of SAR Remote Sensing[M]. Beijing: Science Press, 2008.
[4]	张红, 王超, 刘萌, 等. 极化SAR理论、方法与应用[M]. 北京: 科学出版社, 2015. Zhang Hong, Wang Chao, Liu Meng, et al.. Theory, Approach and Application of Polarimetric SAR[M]. Beijing: Science Press, 2015.
[5]	Dell’Acqua F and Gamba P. Remote sensing and earthquake damage assessment: Experiences, limits, and perspectives[J]. Proceedings of the IEEE, 2012, 100(10): 2876–2890. doi: 10.1109/JPROC.2012.2196404
[6]	Sato M, Chen S W, and Satake M. Polarimetric SAR analysis of Tsunami damage following the March 11, 2011 East Japan Earthquake[J]. Proceedings of the IEEE, 2012, 100(10): 2861–2875. doi: 10.1109/JPROC.2012.2200649
[7]	Chen S W and Sato M. Tsunami damage investigation of built-up areas using multitemporal spaceborne full polarimetric SAR images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(4): 1985–1997. doi: 10.1109/TGRS.2012.2210050
[8]	Chen S W, Wang X S, and Sato M. Urban damage level mapping based on scattering mechanism investigation using fully polarimetric SAR data for the 3.11 East Japan earthquake[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(12): 6919–6929. doi: 10.1109/TGRS.2016.2588325
[9]	吴一戎. 多维度合成孔径雷达成像概念[J]. 雷达学报, 2013, 2(2): 135–142. http://radars.ie.ac.cn/CN/abstract/abstract93.shtml Wu Yi-rong. Concept of multidimensional space joint-observation SAR[J]. Journal of Radars, 2013, 2(2): 135–142. http://radars.ie.ac.cn/CN/abstract/abstract93.shtml
[10]	洪文. 圆迹SAR成像技术研究进展[J]. 雷达学报, 2012, 1(2): 124–135. http://radars.ie.ac.cn/CN/abstract/abstract29.shtml Hong Wen. Progress in circular SAR imaging technique[J]. Journal of Radars, 2012, 1(2): 124–135. http://radars.ie.ac.cn/CN/abstract/abstract29.shtml
[11]	张杰, 张晰, 范陈清, 等. 极化SAR在海洋探测中的应用与探讨[J]. 雷达学报, 2016, 5(6): 596–606. http://radars.ie.ac.cn/CN/abstract/abstract390.shtml Zhang Jie, Zhang Xi, Fan Chen-qing, et al.. Discussion on application of polarimetric synthetic aperture radar in marine surveillance[J]. Journal of Radars, 2016, 5(6): 596–606. http://radars.ie.ac.cn/CN/abstract/abstract390.shtml
[12]	许成斌, 周伟, 丛瑜, 等. 基于峰值区域的高分辨率极化SAR舰船目标特征分析与鉴别[J]. 雷达学报, 2015, 4(3): 367–373. http://radars.ie.ac.cn/CN/abstract/abstract213.shtml Xu Cheng-bin, Zhou Wei, Cong Yu, et al.. Ship analysis and detection in high-resolution Pol-SAR imagery based on peak zone[J]. Journal of Radars, 2015, 4(3): 367–373. http://radars.ie.ac.cn/CN/abstract/abstract213.shtml
[13]	王雪松. 雷达极化技术研究现状与展望[J]. 雷达学报, 2016, 5(2): 119–131. http://radars.ie.ac.cn/CN/abstract/abstract346.shtml Wang Xue-song. Status and prospects of radar polarimetry techniques[J]. Journal of Radars, 2016, 5(2): 119–131. http://radars.ie.ac.cn/CN/abstract/abstract346.shtml
[14]	杨汝良, 戴博伟, 李海英. 极化合成孔径雷达极化层次和系统工作方式[J]. 雷达学报, 2016, 5(2): 132–142. http://radars.ie.ac.cn/CN/abstract/abstract337.shtml Yang Ru-liang, Dai Bo-wei, and Li Hai-ying. Polarization hierarchy and system operating architecture for polarimetric synthetic aperture radar[J]. Journal of Radars, 2016, 5(2): 132–142. http://radars.ie.ac.cn/CN/abstract/abstract337.shtml
[15]	代大海, 廖斌, 肖顺平, 等. 雷达极化信息获取与处理的研究进展[J]. 雷达学报, 2016, 5(2): 143–155. http://radars.ie.ac.cn/CN/abstract/abstract316.shtml Dai Da-hai, Liao Bin, Xiao Shun-ping, et al.. Advancements on radar polarization information acquisition and processing[J]. Journal of Radars, 2016, 5(2): 143–155. http://radars.ie.ac.cn/CN/abstract/abstract316.shtml
[16]	赵春雷, 王亚梁, 阳云龙, 等. 雷达极化信息获取及极化信号处理技术研究综述[J]. 雷达学报, 2016, 5(6): 620–638. http://radars.ie.ac.cn/CN/abstract/abstract389.shtml Zhao Chun-lei, Wang Ya-liang, Yang Yun-long, et al.. Review of radar polarization information acquisition and polarimetric signal processing techniques[J]. Journal of Radars, 2016, 5(6): 620–638. http://radars.ie.ac.cn/CN/abstract/abstract389.shtml
[17]	Huynen J R. Phenomenological Theory of Radar Targets[D]. [Ph.D. dissertation], Delft University of Technology, 1970.
[18]	Cloude S R and Pottier E. An entropy based classification scheme for land applications of polarimetric SAR[J]. IEEE Transactions on Geoscience and Remote Sensing, 1997, 35(1): 68–78. doi: 10.1109/36.551935
[19]	Touzi R. Target scattering decomposition in terms of roll-invariant target parameters[J]. IEEE Transactions on Geoscience and Remote Sensing, 2007, 45(1): 73–84. doi: 10.1109/TGRS.2006.886176
[20]	Paladini R, Martorella M, and Berizzi F. Classification of man-made targets via invariant coherency-matrix eigenvector decomposition of polarimetric SAR/ISAR images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(8): 3022–3034. doi: 10.1109/TGRS.2011.2116121
[21]	Chen S W, Li Y Z, Wang X S, et al.. Modeling and interpretation of scattering mechanisms in polarimetric synthetic aperture radar: Advances and perspectives[J]. IEEE Signal Processing Magazine, 2014, 31(7): 79–89.
[22]	Xu F and Jin Y Q. Deorientation theory of polarimetric scattering targets and application to terrain surface classification[J]. IEEE Transactions on Geoscience and Remote Sensing, 2005, 43(10): 2351–2364. doi: 10.1109/TGRS.2005.855064
[23]	An W T, Cui Y, and Yang J. Three-component model-based decomposition for polarimetric SAR data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(6): 2732–2739. doi: 10.1109/TGRS.2010.2041242
[24]	Yamaguchi Y, Sato A, Boerner W M, et al.. Four-component scattering power decomposition with rotation of coherency matrix[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(6): 2251–2258. doi: 10.1109/TGRS.2010.2099124
[25]	Van Zyl J J, Arii M, and Kim Y. Model-based decomposition of polarimetric SAR covariance matrices constrained for nonnegative eigenvalues[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(9): 3452–3459. doi: 10.1109/TGRS.2011.2128325
[26]	Arii M, Van Zyl J J, and Kim Y. Adaptive model-based decomposition of polarimetric SAR covariance matrices[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(3): 1104–1113. doi: 10.1109/TGRS.2010.2076285
[27]	Neumann M, Ferro-Famil L, and Reigber A. Estimation of forest structure, ground, and canopy layer characteristics from multibaseline polarimetric interferometric SAR data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(3): 1086–1104. doi: 10.1109/TGRS.2009.2031101
[28]	Chen S W, Wang X S, Xiao S P, et al.. General polarimetric model-based decomposition for coherency matrix[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(3): 1843–1855. doi: 10.1109/TGRS.2013.2255615
[29]	Ballester-Berman J D and Lopez-Sanchez J M. Applying the Freeman-Durden decomposition concept to polarimetric SAR interferometry[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(1): 466–479. doi: 10.1109/TGRS.2009.2024304
[30]	Chen S W, Wang X S, Li Y Z, et al.. Adaptive model-based polarimetric decomposition using PolInSAR coherence[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(3): 1705–1718. doi: 10.1109/TGRS.2013.2253780
[31]	Wang C L, Yu W D, Wang R, et al.. Comparison of nonnegative eigenvalue decompositions with and without reflection symmetry assumptions[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(4): 2278–2287. doi: 10.1109/TGRS.2013.2259177
[32]	Li H Z, Wang C, Zhang H, et al.. A unified three-component scattering model for polarimetric coherent target decomposition[J]. International Journal of Remote Sensing, 2012, 33(9): 2868–2891. doi: 10.1080/01431161.2011.622728
[33]	Zhu F Y, Zhang Y H, and Li D. An extension of a complete model-based decomposition of polarimetric SAR data[J]. IEEE Geoscience and Remote Sensing Letters, 2016, 13(2): 287–291. doi: 10.1109/LGRS.2015.2511076
[34]	Deng L and Yan Y N. Improving the Yamaguchi4 decomposition method using selective polarization orientation compensation[J]. Canadian Journal of Remote Sensing, 2016, 42(2): 125–135. doi: 10.1080/07038992.2016.1160774
[35]	Zou B, Zhang Y, Cao N, et al.. A four-component decomposition model for PolSAR data using asymmetric scattering component[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015, 8(3): 1051–1061. doi: 10.1109/JSTARS.2014.2380151
[36]	Wang Y H, Liu H W, and Jiu B. PolSAR coherency matrix decomposition based on constrained sparse representation[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(9): 5906–5922. doi: 10.1109/TGRS.2013.2293663
[37]	Cloude S R and Pottier E. A review of target decomposition theorems in radar polarimetry[J]. IEEE Transactions on Geoscience and Remote Sensing, 1996, 34(3): 498–518.
[38]	张腊梅, 段宝龙, 邹斌. 极化SAR图像目标分解方法的研究进展[J]. 电子与信息学报, 2016, 38(12): 3289–3297. http://youxian.cnki.com.cn/yxdetail.aspx?filename=LDAX20170807001&dbname=CAPJ2015 Zhang Lamei, Duan Baolong, and Zou Bin. Research development on target decomposition method of polarimetric SAR image[J]. Journal of Electronics & Information Technology, 2016, 38(12): 3289–3297. http://youxian.cnki.com.cn/yxdetail.aspx?filename=LDAX20170807001&dbname=CAPJ2015
[39]	Chen S W, Ohki M, Shimada M, et al.. Deorientation effect investigation for model-based decomposition over oriented built-up areas[J]. IEEE Geoscience and Remote Sensing Letters, 2013, 10(3): 273–277.
[40]	Chen S W, Wang X S, and Sato M. Uniform polarimetric matrix rotation theory and its applications[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(8): 4756–4770. doi: 10.1109/TGRS.2013.2284359
[41]	Chen S W, Li Y Z, and Wang X S. A visualization tool for polarimetric SAR data investigation[C]. The 11th European Conference on Synthetic Aperture Radar, Hamburg, Germany, 2016: 579–582.
[42]	Chen S W and Wang X S. Polarimetric coherence pattern: A visualization tool for PolSAR data investigation[C]. The IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China, 2016: 7509–7512.
[43]	Xiao S P, Chen S W, Chang Y L, et al.. Polarimetric coherence optimization and its application for manmade target extraction in PolSAR data[J]. IEICE Transactions on Electronics, 2014, 97(6): 566–574.
[44]	Chen S W, Li Y Z, and Wang X S. Crop discrimination based on polarimetric correlation coefficients optimization for PolSAR data[J]. International Journal of Remote Sensing, 2015, 36(16): 4233–4249. doi: 10.1080/01431161.2015.1079345
[45]	Lee J S, Schuler D L, Ainsworth T L, et al.. On the estimation of radar polarization orientation shifts induced by terrain slopes[J]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(1): 30–41. doi: 10.1109/36.981347
[46]	Chen S W, Wang X S, and Sato M. PolInSAR complex coherence estimation based on covariance matrix similarity test[J]. IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(11): 4699–4710. doi: 10.1109/TGRS.2012.2192937
[47]	陶臣嵩, 陈思伟, 李永祯, 等. 结合旋转域极化特征的极化SAR地物分类[J]. 雷达学报, 录用待刊. doi: 10.12000/JR16131 Tao Chensong, Chen Siwei, Li Yongzhen, et al. Polarimetric SAR terrain classification using polarimetric feature derived from rotation domain[J]. Journal of Radars. doi: 10.12000/JR16131
[48]	Ainsworth T L, Schuler D L, and Lee J S. Polarimetric SAR characterization of man-made structures in urban areas using normalized circular-pol correlation coefficients[J]. Remote Sensing of Environment, 2008, 112(6): 2876–2885. doi: 10.1016/j.rse.2008.02.005
[49]	Yamaguchi Y, Yamamoto Y, Yamada H, et al.. Classification of terrain by implementing the correlation coefficient in the circular polarization basis using X-band POLSAR data[J]. IEICE Transactions on Communications, 2008, E91B(1): 297–301.

Relative Articles

[1]	WANG Zhirui, ZHAO Liangjin, WANG Yuelei, ZENG Xuan, KANG Jian, YANG Jian, SUN Xian. AIR-PolSAR-Seg-2.0: Polarimetric SAR Ground Terrain Classification Dataset for Large-scale Complex Scenes[J]. Journal of Radars, 2025, 14(2): 353-365. doi: 10.12000/JR24237
[2]	YIN Junjun, LUO Jiahao, LI Xiang, DAI Xiaokang, YANG Jian. Ship Detection Based on Polarimetric SAR Gradient and Complex Wishart Classifier[J]. Journal of Radars, 2024, 13(2): 396-410. doi: 10.12000/JR23198
[3]	DING Jinshan, ZHONG Chao, WEN Liwu, XU Zhong. Joint Detection of Moving Target in Video Synthetic Aperture Radar[J]. Journal of Radars, 2022, 11(3): 313-323. doi: 10.12000/JR22036
[4]	HUANG Zhongling, YAO Xiwen, HAN Junwei. Progress and Perspective on Physically Explainable Deep Learning for Synthetic Aperture Radar Image Interpretation（in English）[J]. Journal of Radars, 2022, 11(1): 107-125. doi: 10.12000/JR21165
[5]	YAN Hua, ZHANG Lei, LU Jinwen, XING Xiaoyu, LI Sheng, YIN Hongcheng. Frequency-dependent Factor Expression of the GTD Scattering Center Model for the Arbitrary Multiple Scattering Mechanism[J]. Journal of Radars, 2021, 10(3): 370-381. doi: 10.12000/JR21005
[6]	QUAN Sinong, FAN Hui, DAI Dahai, WANG Wei, XIAO Shunping, WANG Xuesong. Recognition of Ships and Chaff Clouds Based on Sophisticated Polarimetric Target Decomposition[J]. Journal of Radars, 2021, 10(1): 61-73. doi: 10.12000/JR20123
[7]	CUI Xingchao, SU Yi, CHEN Siwei. Polarimetric SAR Ship Detection Based on Polarimetric Rotation Domain Features and Superpixel Technique[J]. Journal of Radars, 2021, 10(1): 35-48. doi: 10.12000/JR20147
[8]	WEI Yangkai, ZENG Tao, CHEN Xinliang, DING Zegang, FAN Yujie, WEN Yuhan. Parametric SAR Imaging for Typical Lines and Surfaces[J]. Journal of Radars, 2020, 9(1): 143-153. doi: 10.12000/JR19077
[9]	WANG Xuesong, CHEN Siwei. Polarimetric Synthetic Aperture Radar Interpretation and Recognition: Advances and Perspectives[J]. Journal of Radars, 2020, 9(2): 259-276. doi: 10.12000/JR19109
[10]	HU Cheng, DENG Yunkai, TIAN Weiming, ZENG Tao. A Compensation Method of Nonlinear Atmospheric Phase Applied for GB-InSAR Images[J]. Journal of Radars, 2019, 8(6): 831-840. doi: 10.12000/JR19073
[11]	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
[12]	Tao Chensong, Chen Siwei, Li Yongzhen, Xiao Shunping. Polarimetric SAR Terrain Classification Using Polarimetric Features Derived from Rotation Domain[J]. Journal of Radars, 2017, 6(5): 524-532. doi: 10.12000/JR16131
[13]	Wu Jiani, Chen Yongguang, Dai Dahai, Pang Bo, Wang Xuesong. Scattering Mechanism Identification Based on Polarimetric HRRP of Manmade Target[J]. Journal of Radars, 2016, 5(2): 174-181. doi: 10.12000/JR16026
[14]	Sun Xun, Huang Pingping, Tu Shangtan, Yang Xiangli. Polarimetric SAR Image Classification Using Multiple-feature Fusion and Ensemble Learning[J]. Journal of Radars, 2016, 5(6): 692-700. doi: 10.12000/JR15132
[15]	Huang Xiaojing, Yang Xiangli, Huang Pingping, Yang Wen. Prototype Theory Based Feature Representation for PolSAR Images[J]. Journal of Radars, 2016, 5(2): 208-216. doi: 10.12000/JR15071
[16]	Yang Ruliang, Dai Bowei, Li Haiying. Polarization Hierarchy and System Operating Architecture for Polarimetric Synthetic Aperture Radar[J]. Journal of Radars, 2016, 5(2): 132-142. doi: 10.12000/JR16013
[17]	Yan Jian, Li Yang, Yin Qiang, Hong Wen. Freeman-Durden Decomposition with Oriented Dihedral Scattering[J]. Journal of Radars, 2014, 3(5): 574-582. doi: 10.3724/SP.J.1300.2014.14057
[18]	Chong Jin-song, Zhou Xiao-zhong. Survey of Study on Internal Waves Detection in Synthetic Aperture Radar Image[J]. Journal of Radars, 2013, 2(4): 406-421. doi: 10.3724/SP.J.1300.2013.13012
[19]	Wu Yi-rong. Concept on Multidimensional Space Joint-observation SAR[J]. Journal of Radars, 2013, 2(2): 135-142. doi: 10.3724/SP.J.1300.2013.13047

Supplements(0)

Cited By

Cited by

Periodical cited type(18)

1.	吴林罡，胡生亮，罗亚松，吴兆东，林立. 浮空角反射体动态雷达目标特性研究. 空天技术. 2025(01): 82-92 .
2.	李铭典，肖顺平，陈思伟. 极化雷达图像目标超分辨率重建研究进展. 电子与信息学报. 2024(05): 1806-1826 .
3.	韩静雯，杨勇，连静，吴国庆，王雪松. 基于极化与距离像特征融合的雷达导引头角反射器鉴别方法. 系统工程与电子技术. 2024(11): 3658-3670 .
4.	祝迪，王福来，庞晨，李永祯. 基于船用导航雷达的舰船与角反组合体极化调控鉴别方法. 雷达学报. 2024(06): 1252-1278 . 本站查看
5.	毕海霞，况祖正，李凡，高静怀，徐晨. 极化SAR图像分类深度学习算法综述. 科学通报. 2024(35): 5108-5128 .
6.	崔兴超，李郝亮，付耀文，陈思伟，粟毅. 空间目标散射结构极化旋转域辨识. 电子与信息学报. 2023(06): 2105-2114 .
7.	陈思伟，周鹏. SAR图像对抗攻击的进展与展望. 信息对抗技术. 2023(Z1): 171-188 .
8.	李郝亮，陈思伟. 极化测量误差对人造目标散射解译性能的影响研究. 现代雷达. 2022(01): 1-8 .
9.	李郝亮，陈思伟，王雪松. 海面角反射器的极化旋转域特性研究. 系统工程与电子技术. 2022(07): 2065-2073 .
10.	吴国庆，陈思伟，李永祯，王雪松. 人造目标散射结构的零极化辨识与应用. 电波科学学报. 2022(05): 733-742+760 .
11.	赵锋，徐志明，刘蕾，艾小锋. 弹道目标特征提取研究现状与展望. 信息对抗技术. 2022(03): 15-32 .
12.	于腾，王锐，李沐阳，胡程. 宽带全极化垂直昆虫雷达设计及校准关键技术研究. 信号处理. 2021(02): 222-233 .
13.	崔兴超，粟毅，陈思伟. 融合极化旋转域特征和超像素技术的极化SAR舰船检测. 雷达学报. 2021(01): 35-48 . 本站查看
14.	肖顺平，陈思伟. 雷达极化信息处理的启发式研讨教学研究. 电气电子教学学报. 2021(06): 71-75 .
15.	杨成财，余慧庄，龙郝明. 基于SVM和能量最小化的PolSAR图像分类方法. 电子测量技术. 2020(03): 146-152 .
16.	王雪松，陈思伟. 合成孔径雷达极化成像解译识别技术的进展与展望. 雷达学报. 2020(02): 259-276 . 本站查看
17.	王宇，禹卫东，刘秀清. 基于极化特征参数和极化干涉最优参数的改进四元素分解方法. 电子与信息学报. 2019(12): 2881-2888 .
18.	孙翔，宋红军，王宇，李宁. 基于高分辨率全极化SAR图像的取向角校正方法. 雷达学报. 2018(04): 465-474 . 本站查看

Other cited types(13)

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(5226) PDF downloads(739)