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基于二次散射的舰船目标SAR图像仿真 被引量:2

SAR Image Simulation of Ship Targets Based on Double-Bounce Reflection
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摘要 基于合成孔径雷达(SAR)的工作过程,对舰船目标进行基于回波信号的SAR成像仿真。目标建模时采用小面单元模型,将建好的精细舰船3D模型,根据SAR系统参数和分辨率要求划分为小面单元,然后对面元进行散射截面的计算。在计算目标散射截面时,结合射线追踪法充分考虑了目标的一次散射,二次散射效应,使仿真图像更加符合真实的SAR图像特征。根据面元散射截面和位置信息,结合雷达工作过程,生成回波。再运用RD成像算法处理回波,得到最终的仿真图像。将实验仿真图像与真实SAR图像对比,验证文中仿真方法的合理性。 Based on the synthetic aperture radar(SAR)working process,the SAR imaging simulation of ship targets is made by use of the echo signals.The precise 3Dship model is divided into facets according to the SAR system parameters and resolution.When calculating the RCS,single reflection and double-bounce reflection are both considered in combination with ray tracing method.Combined with the radar working process,echo signals are generated according to the surface scattering cross section and the location information.The echo signals are processed by the RD algorithm to achieve imaging simulation.The simulation images are compared with the real SAR images to verify the effectiveness of the simulation method.
出处 《雷达科学与技术》 北大核心 2015年第1期37-43,50,共8页 Radar Science and Technology
基金 "泰山学者"建设专项工程经费
关键词 二次散射 舰船 合成孔径雷达 图像仿真 double-bounce reflection ships synthetic aperture radar(SAR) imaging simulation
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参考文献12

  • 1KNAPSKOG A O, BROVOLL S, TORVIK B. Char- acteristics of Ships in Harbour Investigated in Simul- taneous Images from TerraSAR-X and PicoSAR[C]//Proceedings of the IEEE International Radar Confer- ence, Washington, DC, USA [s. n.], 2010 : 422-427. M.
  • 2ARGARIT G, TABASCO A. Ship Classification in Single-Pol SAR Images Based on Fuzzy Logic [J]. IEEE Trans on Geoscience and Remote Sensing, 2011, 49(8) 13129-3138.
  • 3韦志峰,潘梦莹.3dsmax综合建模全实例解析[M].北京:中国青年出版社,2007.
  • 4张显峰,杨露菁,张伟.舰船目标SAR图像仿真方法研究[J].舰船电子工程,2011,31(7):102-104. 被引量:5
  • 5张显峰,杨露菁,罗兵.基于Vega的舰船SAR图像仿真[J].舰船电子工程,2011,31(6):122-123. 被引量:4
  • 6FERRO A, BRUNNER D, BRUZZONE L, et al. On the Relationship Between Double Bounce and the Ori- entation of Buildings in VHR SAR Images[J]. IEEE Geoscienee and Remote Sensing Letters, 2011, 8(4): 612-616.
  • 7AUER S, HINZ S, BAMLER R. Ray-Tracing Simu- lation Techniques for Understanding High-Resolution SAR Images[J]. IEEE Trans on Geoscience and Re- mote Sensing, 2010, 48(3):1445-1456.
  • 8ZHANG H, TIAN X, WANG C, et al. Merchant Vessel Classification Based on Scattering Component Analysis for COSMO-SkyMed SAR Images[J]. IEEE Geoscience and Remote Sensing Letters, 2013, 10 (6) :1275-1279.
  • 9ZHANG M, ZHAO Y W, CHEN H, et al. SAR Imaging Simulation for Composite Model of Ship on Dynamic Ocean SceneEC ff Progress In Electromag- netics Research, [S. 1. ]:[s. n. ], 2011:395-412.
  • 10TANG Kan, SUN Xian, SUN Hao, et al. A Geo- metrical-Based Simulator for Target Recognition in High-Resolution SAR Images[J]. IEEE Geoscience and Remote Sensing Letters, 2012, 9(5):958-962.

二级参考文献36

  • 1陈宏希.基于边缘保持平滑滤波的Canny算子边缘检测[J].兰州交通大学学报,2006,25(1):86-90. 被引量:43
  • 2王飞,赵广州,张天序.基于Vega的舰船模型多尺度多视点提取技术[J].计算机与数字工程,2006,34(12):26-29. 被引量:3
  • 3牛力丕,毛士艺,陈炜.基于Hausdorff距离的图像配准研究[J].电子与信息学报,2007,29(1):35-38. 被引量:21
  • 4Zitova B, Flusser J. Image registration methods: a survey[J]. Image Vision Computing ,2003,21(11) : 977 - 1000.
  • 5Son H J, Kim S H, Kim J S. Text image matching without language model using a Hausdorff distance[J]. Information Processing and Management,2008,44(3) :1189 - 1200.
  • 6Vivek E P, Sudha N. Robust Hausdorff distance measure for face recognition[J]. Pattern Recognition ,2007 ,40(2) :431- 442.
  • 7Park S C, Lee S W. Object tracking with probabilistic Hausdorffdistance matching[J]. Lecture Notes in CoTnputer Science, 2005, 44(1) :233 - 242.
  • 8Huttenlocher D P, Klanderman G A, Rueklidge W J. Comparing images using the Hausdorff distance[J]. IEEE Trans. on Pattern Analysis and Machine Intelligence ,1993,15(9) :850 - 863.
  • 9Dubuisson M P, Jain A K. A modified hausdorff distance for object matching[C]// Proc. of the International Conference on Pattern Recognition, 1994 : 566 - 568.
  • 10Sire D G, Kwon O K, Park R H. Object matching algorithms using robust hausdorff distance measures[J]. IEEE Trans. on Image Processing, 1999,8(3) :425 - 429.

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