[1] 皮亦鸣, 杨建宇, 付毓生, 等. 合成孔径雷达成像原理 [M]. 成都: 电子科技大学出版社, 2007: 1-3. (Pi Yi-ming, Yang Jian-yu, Fu Yu-sheng, et al.Imaging theory for Synthetic Aperture Radar [M]. Chendu: University of Electronic Science & Technology Press, 2007: 1-3.) [2] 黄瑾. 基于多波段多极化SAR数据的黄河口湿地分类研究 [D]. 东营: 中国石油大学(华东), 2011: 21-32. (Huang Jin.Classification of the Yellow River Estuary Wetland Based on Multiband and Multipolarization SAR Data [D]. Dong Ying: China University of Pertroleum, 2001: 21-32.) [3] 程千, 王崇倡, 张继超. RADARSAT-2全极化SAR数据地表覆盖分类[J]. 测绘工程, 2015, 24(4): 61-65. (Cheng Qian, Wang Cong-chang, Zhang Ji-chao.Land cover classification using RADARSAT-2 full polarimetric SAR data[J]. Engineering of Surveying and Mapping, 2015, 24(4): 61-65.) [4] Shiv M, Anup D, Dipan H, et al.Monitoring and retrieval of vegetation parameter using multi-frequency polarimetric SAR data[C]// The 3rd International Asia-Pacific Conference on Synthetic Aperture Radar, Seoul, Korea. USA: IEEE, 2011: 1-4. [5] 王之禹, 朱敏慧, 白有天. 基于最优状态的多波段全极化SAR数据ML分类方法[J]. 电子与信息学报, 2001, 23(5): 507-511. (Wang Zhi-yu, Zhu Min-hui, Bai You-tian.Optimal state based ML classification method for multi-band and full-polarization SAR data[J]. Journal of Electronics and Information Technology, 2001, 23(5): 507-511.) [6] Notarnicola C, Ventura B, Posa F.Adaptive Bayesian algorithm for vegetated field parameters extraction by using multi-frequency and multi-polarimetric SAR image[C]// IEEE International Conference on Geoscience and Remote Sensing Symposium, Barcelona, Spain. USA: IEEE, 2007: 3401-3404. [7] 刘向君, 常文革, 常玉林. 基于决策级融合的多波段SAR目标检测方法[J]. 现代雷达, 2007, 29(2): 22-25. (Liu Xiang-jun, Chang Wen-ge, Chang Yu-lin.A Multi-band SAR Target Detection Method Based on Decision Fusion[J] Modern Radar, 2007, 29(2): 22-25.) [8] 邬伯才, 江凯, 陈仁元. 多波段多极化机载SAR系统研制 [C]// 第十届全国雷达学术年会论文集. 北京: 国防工业出版社, 2008: 972-976. (Wu Bo-cai, Jiang Kai, Chen Ren-yuan, Research of Multi-band and Multi-polarimetric Airborne SAR system [C]// Proceedings of 10th annual radar conference. Beijing: National defense industry press, 2008: 972-976.) [9] 刘法龙, 刘俊, 赵宗贵, 等. 基于Creator和Vega的红外/SAR成像仿真[J]. 现代电子技术, 2014, 37(4): 104-107. (Liu Fa-long, Liu Jun, Zhao Zong-gui, et al.IR/SAR imaging simulation based on Creator and Vega[J]. Modern Electronics Technique, 2014, 37(4): 104-107.) [10] 牛杰, 沈晓峰. 基于Creator和Vega的SAR成像仿真研究[J]. 空间电子技术, 2010, 7(3): 45-48. (Niu Jie, Shen Xiao-feng.Research on the Simulation of SAR Image Based on Creator and Vega[J]. Space Electronics Technology, 2010, 7(3): 45-48.) [11] Qun Zhao, Principe J C.Support vector machines for SAR automatic target recognition[J]. IEEE Transactions on Aerospace and Electronic Systems (S0018-9251), 2001, 37(2): 643-654. [12] Thiagarajan J J, Ramamurthy K N, Knee P.Sparse representations for automatic target classification in SAR images[C]// The 4th International Symposium on Communications, Control and Signal Processing, Limassol, Cyprus. USA: IEEE, 2010: 1-4. [13] Amoon M, Rezai-rad G, Daliri M R. PSO-based optimal selection of Zernike Moments for target discrimination in high-resolution SAR imagery[J]. Journal of the Indian Society of Remote Sensing (S0255-660X), 2014, 42(3): 483-493. [14] 刘俊. 面向船舶避碰预警的红外运动船舶检测与跟踪[J]. 光电工程, 2010, 37(9): 8-13. (Liu Jun.Moving Ship Detection and Tracking from Infrared Image for Collision-avoidance of Ships[J]. Opto-Electronic Engineering, 2010, 37(9): 8-13.) [15] Clausi D A.Comparison and fusion of co-occurrence, Gabor, and MRF texture features for classification of SAR sea ice imagery[J]. Atmosphere-ocean (S0705-5900), 2001, 39(3): 183-194. [16] Khanesar M A, Teshnehlab M, Shoorehdeli M A.A novel binary particle swarm optimization[C]// Proceedings of the 15th Mediterranean Conference on Control & Automation, Athens, Greece. USA: IEEE, 2007: 1-6. |