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內容簡介: |
本书共计11章,第1章对合成孔径雷达(SAR)目标识别进行了概述;第2章介绍了基于局部保持特性和混合高斯分布的SAR目标识别;第3章介绍了基于局部保持特性和Gamma分布的SAR目标识别;第4章介绍了基于结构保持投影的SAR目标识别;第5章介绍了基于类别稀疏表示的SAR目标识别;第6章介绍了基于乘性稀疏表示和Gamma分布的SAR目标识别;第7章介绍了基于判别统计字典学习的SAR目标识别;第8章介绍了于Dempster-Shafer证据理论融合多稀疏描述和样本统计特性的SAR目标识别;第9章介绍了基于Dempster-Shafer证据理论和稀疏表示的SAR目标识别;第10章介绍了基于两阶段稀疏结构表示的SAR目标识别;第11章探讨了未来合成孔径雷达目标识别可能的发展方向。
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關於作者: |
刘明,工学博士,副教授,硕士生导师。2009年获西安电子科技大学信息对抗技术专业工学学士学位,2015年获西安电子科技大学模式识别与智能系统专业工学博士学位。2019年-2020年为加拿大McMaster University访学学者。主要研究方向为:目标检测与目标识别。入选陕西省科协青年人才托举计划,获国际无线电科学联盟(URSI)”青年科学家”奖,获陕西省计算机学会”计算机领域优秀青年专家”称号。主持和参与了包括国家自然科学基金、国家重大基础研究计划、装备预先研究、陕西省自然科学基金等10余项国家级和省部级科研项目。发表学术论文60余篇,授权国家发明专利10项(部分已转化)。
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目錄:
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第1 章 绪论························································································1 1.1 研究背景及研究意义··································································1 1.2 国内外研究现状········································································3 1.3 本书内容介绍········································································.10 第2 章 基于局部保持特性和混合高斯分布的SAR 图像目标识别··················.14 2.1 算法概述··············································································.14 2.2 局部保持投影算法··································································.15 2.3 基于LPP-GMD 算法的SAR 图像目标识别···································.16 2.3.1 基于混合高斯分布的似然函数建模····································.17 2.3.2 基于局部保持特性的先验函数建模····································.17 2.3.3 参数估计·····································································.18 2.4 试验结果与分析·····································································.22 2.5 本章小结··············································································.26 第3 章 基于局部保持特性和Gamma 分布的SAR 图像目标识别··················.27 3.1 算法概述··············································································.27 3.2 SAR 图像的乘性相干斑模型······················································.28 3.3 基于LPP-Gamma 算法的SAR 图像目标识别·································.29 3.3.1 基于Gamma 分布构建似然函数········································.29 3.3.2 基于局部保持特性构建先验函数·······································.30 3.3.3 参数估计·····································································.33 3.4 试验结果与分析·····································································.37 3.4.1 SAR 图像目标识别结果··················································.37 3.4.2 修正相似度矩阵的有效性验证··········································.39 3.5 本章小结··············································································.41 第4 章 基于结构保持投影的SAR 图像目标识别·······································.42 4.1 算法概述··············································································.42 4.2 基于CDSPP 算法的SAR 图像目标识别·······································.43 4.2.1 CDSPP 算法·································································.43 4.2.2 差异度矩阵分析····························································.45 4.3 试验结果与分析·····································································.49 4.3.1 目标的类别识别····························································.51 4.3.2 目标的型号识别····························································.53 4.3.3 构建差异度矩阵的优势···················································.57 4.4 本章小结··············································································.59 第5 章 基于类别稀疏表示的SAR 图像目标识别·······································.60 5.1 算法概述··············································································.60 5.2 SAR 图像的稀疏表示模型·························································.61 5.3 SAR 图像的类别稀疏表示模型···················································.62 5.3.1 方位角敏感特性····························································.62 5.3.2 测试样本建模·······························································.64 5.3.3 稀疏向量求解·······························································.66 5.4 基于LSR 算法的SAR 图像目标识别···········································.67 5.5 试验结果与分析·····································································.70 5.5.1 目标的类别识别····························································.70 5.5.2 目标的型号识别····························································.72 5.6 本章小结··············································································.76 第6 章 基于乘性稀疏表示和Gamma 分布的SAR 图像目标识别··················.77 6.1 算法概述··············································································.77 6.2 乘性稀疏表示算法··································································.78 6.3 试验结果与分析·····································································.80 6.3.1 目标的类别识别····························································.81 6.3.2 目标的型号识别····························································.82 6.4 本章小结··············································································.88 第7 章 基于判别统计字典学习的SAR 图像目标识别·································.89 7.1
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