电子学报 ›› 2022, Vol. 50 ›› Issue (3): 726-752.DOI: 10.12263/DZXB.20211068

所属专题: 长摘要论文

• 综述评论 • 上一篇    下一篇

面向不同雷达任务的认知波形优化综述

余若峰, 杨威, 付耀文, 张文鹏   

  1. 国防科技大学电子科学学院,湖南 长沙 410073
  • 收稿日期:2021-08-11 修回日期:2021-12-29 出版日期:2022-03-25
    • 作者简介:
    • 余若峰 男,1993年生,广东汕头人.博士研究生.研究方向为智能感知与处理.E-mail:yuruofeng0819@sina.com
      杨 威(通讯作者) 男,1985年生,江西丰城人.国防科技大学电子科学学院副教授.主要研究方向为认知雷达信号处理、雷达目标联合检测、跟踪与识别.E-mail:yw850716@sina.com
      付耀文 男,1976年生,江西奉贤人.国防科技大学电子科学学院研究员.主要研究方向为雷达信号处理、信息融合. E-mail:fuyaowen@sina.com
      张文鹏 男,1989年生,广东普宁人.博士,讲师.研究方向为雷达目标微动反演与识别.
    • 基金资助:
    • 国家自然科学基金 (61871384); 中国博士后科学基金第3批特别资助 (2021TQ0084); 湖南省自然科学基金青年基金 (2021JJ40699)

A Review on Cognitive Waveform Optimization for Different Radar Missions

YU Ruo-feng, YANG Wei, FU Yao-wen, ZHANG Wen-peng   

  1. College of Electronic Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China
  • Received:2021-08-11 Revised:2021-12-29 Online:2022-03-25 Published:2022-03-25
    • Supported by:
    • National Natural Science Foundation of China (61871384); China Postdoctoral Science Foundation 3rd Special Grant (2021TQ0084); Youth Fund of Natural Science Foundation of Hunan Province, China (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.

关键词: 认知雷达, 波形优化, 波形设计, 雷达任务

Abstract:

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 radar 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 introduced, and the main research contents and progress of cognitive waveform optimization oriented to detection, tracking, imaging, 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 potential research area in waveform optimization techniques, including knowledge validity evaluation, artificial intelligence based cognitive waveform optimization, General metrics, knowledge-aided optimization algorithms, etc.

Key words: cognitive radar, waveform optimization, waveform design, radar mission

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