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
- 电子学报 2022年50卷第3期 页码：726-752
- 作者机构：
国防科技大学电子科学学院，湖南长沙 410073
- 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." ]
- 基金信息：国家自然科学基金(61871384;61901487);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)
DOI：10.12263/DZXB.20211068
中图分类号： TN95收稿：2021-08-11，
修回：2021-12-29，
纸质出版：2022-03-25
- 稿件说明：
移动端阅览
余若峰,杨威,付耀文等.面向不同雷达任务的认知波形优化综述[J].电子学报,2022,50(03):726-752.
YU Ruo-feng,YANG Wei,FU Yao-wen,et al.A Review on Cognitive Waveform Optimization for Different Radar Missions[J].ACTA ELECTRONICA SINICA,2022,50(03):726-752.
余若峰,杨威,付耀文等.面向不同雷达任务的认知波形优化综述[J].电子学报,2022,50(03):726-752. DOI： 10.12263/DZXB.20211068.
YU Ruo-feng,YANG Wei,FU Yao-wen,et al.A Review on Cognitive Waveform Optimization for Different Radar Missions[J].ACTA ELECTRONICA SINICA,2022,50(03):726-752. DOI： 10.12263/DZXB.20211068.
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.
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.
关键词
Keywords
references
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