面向不同雷达任务的认知波形优化综述  

A Review on Cognitive Waveform Optimization for Different Radar Missions

作　　者：余若峰 杨威 付耀文 张文鹏 YU Ruo-feng;YANG Wei;FU Yao-wen;ZHANG Wen-peng(College of Electronic Science and Technology,National University of Defense Technology,Changsha,Hunan 410073,China)

机构地区：[1]国防科技大学电子科学学院,湖南长沙410073

出　　处：《电子学报》2022年第3期726-752,共27页Acta Electronica Sinica

基　　金：国家自然科学基金(No.61871384,No.61901487);中国博士后科学基金第3批特别资助(No.2021TQ0084);湖南省自然科学基金青年基金(No.2021JJ40699)。

摘　　要：传统雷达系统的发射机与接收机采用开环工作模式,在动态复杂环境下探测目标时缺乏灵活性和稳健性.借鉴生物认知学习过程,认知雷达可以感知动态环境和目标信息,通过发射和接收端闭环反馈控制,实现全自适应探测和信号处理.本文介绍了认知雷达波形优化的基本框架,递进地梳理了面向检测、跟踪、成像、分类任务以及抗干扰认知波形优化的主要研究内容和研究进展,为面向单一任务及联合多任务的波形优化技术研究提供了纵向和横向的对比视角.在已有研究的基础上,本文分析了认知雷达波形优化的优势和挑战,指出认知波形优化技术中潜在的研究方向,包括知识有效性评价、人工智能认知波形优化、通用度量准则、知识辅助的高效优化算法等方面.The transmitter and receiver of traditional radar system use open-loop mode,which is lack of flexibility and robustness when sensing targets in dynamic environment.Based on biological cognitive learning process,cognitive ra⁃dar can sense dynamic environment and target information,and realize fully adaptive processing by closed-loop feedback control of transmitter and receiver.In this paper,the basic framework of cognitive radar waveform optimization is intro⁃duced,and the main research contents and progress of cognitive waveform optimization oriented to detection,tracking,im⁃aging,classification and anti-jamming are summarized,which provides a vertical and horizontal comparative perspective for waveform optimization technology research oriented to single mission and joint multi-missions.On the basis of existing research,analysis of the cognitive radar waveform optimization advantages and challenges,points out that the cognitive po⁃tential research area in waveform optimization techniques,including knowledge validity evaluation,artificial intelligence based cognitive waveform optimization,General metrics,knowledge-aided optimization algorithms,etc.

关 键 词：认知雷达 波形优化 波形设计 雷达任务 

分 类 号：TN95[电子电信—信号与信息处理]