MS004318-雷达成像与探测技术

研究生课程开设申请表

开课院（系、所）：金沙js800000

课程申请开设类型： 新开☑     重开□     更名□（请在□内打勾，下同）

一、课程介绍（含教学目标、教学要求等）（300字以内）

本课程是面向微波和信号交叉方向开设的一门专业选修课程，结合雷达成像探测技术的具体应用，主要介绍和推广雷达高分辨成像、参数估计和信息反演等前沿技术。课程基于雷达信号处理和雷达成像处理关键技术，展开介绍和探讨现有成像雷达体制的信号处理、高分辨成像以及目标信息获取等先进技术，推广雷达成像技术的具体实际应用。本课程的主要任务是通过讲课和练习，使学生掌握微波和信号等专业基础知识，掌握雷达成像系统一般问题的解决方法。同时，课程实施系列改革，探索新的教学理念、尝试更好的教学模式，将爱国情怀、社会责任、文化自信、人文情怀、工程伦理、工匠精神等诸多内涵注入教育环节中。结合实际应用，让学生了解国家相关的航空航天建设，激发学生的社会主义国防建设热情，以便后续更好的投入社会主义建设中。

二、教学大纲（含章节目录）：（可附页）

课程的教学内容与学时分配如下：

1. 雷达成像和探测技术概括：（4学时）

了解雷达成像探测技术发展现状，掌握雷达成像基本原理、基本功能，并理解合成孔径雷达的概念。

2. 合成孔径雷达成像技术：（6学时）

理解和掌握合成孔径雷达成像基本原理和算法流程。

3. 逆合成孔径雷达成像技术：（6学时）

理解和掌握逆合成孔径雷达成像基本原理和算法流程。

4. 雷达高分辨成像三维成像技术：（4学时）

掌握SAR三维成像基本原理，并了解SAR三维成像技术在实际中的应用。

5. 雷达成像和探测技术总结：（2学时）

回顾和总结本课程讲解的各种雷达成像技术，并对后续的工作进行展望。

6. 浅议雷达成像和探测技术特点和发展趋势：（2课时）

浅议雷达成像和探测技术特点和发展趋势，增加同学对于雷达成像技术的进一步了解和认知。

7. 浅议雷达成像和探测最新技术：（2学时）

浅议雷达成像和探测最新技术，探讨新技术特征和应用。

8. 匹配滤波成像实验：（2学时）

结合雷达成像脉冲压缩技术，进行匹配滤波成像实验，具体实现其中一个典型的demon。

9. 合成孔径雷达成像实验：（2学时）

结合合成孔径雷达成像技术，进行合成孔径雷达成像实验，具体实现其中一个典型的demon。

10. 逆合成孔径雷达成像实验：（2学时）

结合逆合成孔径雷达成像技术，进行逆合成孔径雷达成像实验，具体实现其中一个典型的示例。

三、教学周历

注：1.以上一、二、三项内容将作为中文教学大纲，在研究生院中文网页上公布，四、五内容将保存在研究生院。2.开课学期为：春季、秋季或春秋季。3.授课语言为：汉语、英语或双语教学。4.适用学科范围为：公共，一级，二级，三级。5.实践环节为：实验、调研、研究报告等。6.教学方式为：讲课、讨论、实验等。7.学位课程考试必须是笔试。8.课件地址指在网络上已经有的课程课件地址。9.主讲教师简介主要为基本信息（出生年月、性别、学历学位、专业职称等）、研究方向、教学与科研成果，以100至500字为宜。

四、主讲教师简介：

徐刚，博士，副教授，博导。2015年博士毕业于西安电子科技大学，2015至2016年在新加坡南洋理工大学做博士后研究，2016年入职于金沙js800000毫米波国家重点实验室。主要研究方向为雷达成像技术、遥感图像处理、稀疏信号处理、统计机器学习、人工智能等。具体研究工作：1）高分辨雷达系统设计与成像算法理论研究，聚焦雷达成像新体制设计、成像算法与成像应用；2）毫米波雷达技术，涉及雷达系统设计、雷达信号/成像处理、阵列信号处理、目标跟踪等关键技术；3）统计机器学习理论研究及其在分布式网络雷达成像、图像处理、目标识别等智能信息获取与解译中的应用。主持承担和重点参与国家自然科学基金、国家973计划课题、国家863计划课题、国际合作等多项国家级项目。讲授本科专业课程《微波遥感探测新技术》。

五、任课教师信息（包括主讲教师）：

六、课程开设审批意见

说明：1．研究生课程重开、更名申请也采用此表。表格下载：http:/seugs.seu.edu.cn/down/1.asp

2．此表一式三份，交研究生院、院（系）和自留各一份，同时提交电子文档交研究生院。

Application Form For Opening Graduate Courses

School (Department/Institute)：

Course Type: New Open ☑   Reopen □   Rename □（Please tick in □, the same below）

1. Course Introduction (including teaching goals and requirements) within 300 words:

Thiscourse is related to the subject of microwave and signal processing. It refers to the high-resolution radar imaging and parameter inversion, incorporating with the application of radar imaging and remote sensing. Based on the technologies of radar signal processing and radar imaging, it introduces and investigates the advanced radar imaging system design, imaging technique and target parameter estimation. In particular, it also involves the most popular technologies of compressive sensing, machine learning and deep learning, which is typically applied to radar imaging. Benefiting from this course, you can learn about the basic knowledge of radar direction and application.

2. Teaching Syllabus (including the content of chapters and sections. A sheet can be attached):

1. Introduction to radar imaging and remote sensing (4)

2. Synthetic aperture radar imaging technology (6)

3. Inverse synthetic aperture radar imaging technology (6)

4. Three-dimensional radar imaging technology (4)

5. Summary of radar imaging and remote sensing (2)

6. Discussion on the trend of radar imaging and remote sensing (2)

7. Introduction the new theory of radar imaging and remote sensing (2)

8. Experiment on matched filtering (2)

9. Experiment on synthetic aperture radar imaging (2)

10. Experiment on inverse synthetic aperture radar imaging (2)

3. Teaching Schedule:

Note: 1.Above one, two, and three items are used as teaching Syllabus in Chinese and announced on the Chinese website of Graduate School. The four and five items are preserved in Graduate School.

 2. Course terms: Spring, Autumn , and Spring-Autumn term.   

 3. The teaching languages for courses: Chinese, English or Chinese-English.  

 4. Applicable range of discipline: public, first-class discipline, second-class discipline, and third-class discipline.  

 5. Practice includes: experiment, investigation, research report, etc.  

 6. Teaching methods: lecture, seminar, practice, etc.  

 7. Examination for degree courses must be in paper.  

 8. Teaching material websites are those which have already been announced.  

 9. Brief introduction of chief lecturer should include: personal information (date of birth, gender, degree achieved, professional title), research direction, teaching and research achievements. (within 100-500 words)  

4. Brief Introduction of Chief lecturer:

 XU Gang, IEEE member and CIE member, received the Ph.D degree in electrical engineering from Xidian University in 2015. From 2015 to 2016, he was a full-time Postdoctoral Research Fellow with the School of Electrical and Electronic Engineering (EEE), Nanyang Technological University (NTU), Singapore. Since 2016, he is an associate professor with the State Key Laboratory of Millimeter Waves, Southeast University. His major research interests include radar imaging technology, image processing in remote sensing, sparse signal processing, statistical machine learning, artificial intelligence and etc. The details are: 1) high-resolution radar system design and imaging technology/theory, focusing on novel imaging system design, advanced imaging technology and application; 2) millimeter wave radar technology, including radar system design, radar signal/imaging processing, array signal processing, target tracking; 3) statistical machine learning theory and intelligent information extraction and interpretation technology in distributed network, radar imaging, image processing and target recognition. He has fully been in charge of and participated in several projects of national grade, such as National Natural Science Foundation of China, national 973 projection, national 863 project, intentional cooperation and etc. His Ph.D thesis has won the university’s excellent graduation thesis, Shaanxi province’s excellent graduation thesis and the nomination award of first CIE excellent graduation thesis. In recent years, he has first authored over 10 technical publications on the international TOP journals, such as IEEE Geoscience and Remote Sensing Magazine, IEEE Trans. on Geoscience and Remote Sensing and IEEE Trans. on Imaging Processing.

5. Lecturer Information (include chief lecturer)