雷达协同认知成像方法与关键技术

The research on space target detection and recognition theories and relevant key technologies, is of great significance in both guaranteeing China’s territory air defense security and promoting the nation’s space technology development and space peaceful use. Currently, it is still difficult to realize the rapid and stable imaging of complex space target with the existing radar imaging technologies. Meanwhile, there are also great difficulties in realizing space multi-target imaging. With specific applications oriented like space target cataloging and anti-missile target recognition, this project is based on the existed research of our project group in space target imaging and cognitive radar imaging. Closely following the development trend of network radar and intelligent radar, our project group aims at further researches on collaboratively cognitive imaging methods and relevant key technologies based on radar network. By establishing collaboratively cognitive imaging model of radar network, the corresponding imaging mechanism is investigated with the thought of cognitive feedback and closed-loop optimization embedded. Collaboratively cognitive imaging methods of radar network can then be systematically proposed. This project is expected to obtain original findings in collaboratively cognitive imaging theories of radar network and relevant signal and information processing methods, occupying the international academic front in collaboratively cognitive radar imaging research. The research of this project can prospectively provide solid theoretical and technical supports for improving the nation’s space target detection and recognition capabilities. Meanwhile, it can provide theoretical basis and technological solutions for new intelligent and systematic radar imaging systems.

开展空间目标探测与识别理论及相关关键技术研究，对保障我国国土防空安全、促进国家空间技术发展以及空间和平利用均具有十分重要的意义。现有雷达成像技术既难以实现对空间复杂目标的快速稳定成像，在空间多目标高效成像方面也存在很大困难。面向空间目标编目、防空反导目标识别等具体应用，本项目组在长期开展空间目标成像、认知成像研究的基础上，瞄准未来雷达网络化、智能化发展趋势，进一步研究基于组网雷达的协同认知成像方法及其关键技术。通过建立组网雷达协同认知成像模型，研究基于认知反馈与闭环优化的组网雷达协同成像机理，提出系统的组网雷达协同认知成像方法，在组网雷达协同认知成像理论及其信号与信息处理方法方面取得原创性成果，形成我国在组网雷达协同认知成像领域的国际学术前沿地位。本项目的研究将为提升我国空间目标探测与识别能力提供理论和方法支撑，同时也将为智能化、体系化雷达成像新体制的研究和发展提供理论依据和技术手段。

本项目瞄准未来雷达网络化、智能化发展趋势，深入研究了基于组网雷达的协同认知成像方法及其关键技术，完成了微波暗室环境下相关基础理论与方法的实验验证，部分研究成果在实际装备中得到了验证和应用，为智能化、体系化雷达成像新体制的研究和发展提供了理论依据和技术手段。项目主要取得了以下研究成果：（1）建立了组网雷达协同认知成像处理模型；（2）突破了认知成像与特征提取、组网雷达资源认知管理等一系列关键技术，在暗室环境中完成了部分关键技术的实验验证，并形成了实验室演示验证平台系统，实验表明，微动目标成像所需积累时间由百毫秒级缩短至毫秒级，视频三维成像帧率达到12.5帧/秒，雷达系统资源利用效率可提升45%以上；（3）在国内外刊物和会议发表论文134篇，其中SCI论文77篇，出版了首部以认知成像为主题的专著并获得国家科学技术学术著作出版基金项目资助，在《雷达学报》组织了出版了“雷达微多普勒分析技术”专刊；（4）申报发明专利53项，完成了相应的计算与仿真，开发的3套软件系统已在多家单位应用；（5）培养青年教师7名、博士研究生6名、硕士研究生29名，其中1人入选“万人计划”青年拔尖人才，1人入选全军学科拔尖人才并获得国务院政府特殊津贴，3人入选军队青年科技英才，1人获中国电子教育学会优秀博士学位论文奖，1人获2018 IET Radar Conference Best Paper Award；（6）“××成像技术及应用”获国家技术发明二等奖，“××成像关键技术”获军队科技进步一等奖，“非合作运动目标高分辨雷达成像研究”获教育部自然科学一等奖。