期刊文献+

微波光子认知雷达技术 被引量:2

A Microwave Photonic Cognitive Radar
下载PDF
导出
摘要 针对宽带微波光子雷达易被外界电磁信号干扰,难以在复杂电磁环境下对多样化目标进行高速探测与识别的关键难题,本文提出一种能融合多个机会频带以实现高分辨率探测的微波光子认知雷达系统架构。探讨了与微波光子认知雷达系统相关的微波光子宽带实时频谱侦测、可重构波形产生和稀疏频带成像处理等关键技术,论证了方案的可行性。该方案充分发挥了光子技术的宽带承载、实时处理以及灵活可重构的优势,可同时提升雷达的分辨率和环境适应能力,有望为未来智能化装备提供清晰、可靠、智能的全天候探测手段。 Due to the broadband nature,microwave photonic radars are vulnerable to external electromagnetic interference and therefore difficult to work in complex electromagnetic environment.This paper proposes a novel microwave photonic cognitive radar that can achieve high-resolution detection using multiple opportunistic sparse frequency bands.Key techniques for the microwave photonic cognitive radar,such as real-time and broadband microwave photonic spectrum monitoring,reconfigurable waveform generation,and sparse imaging are discussed.The feasibility of the radar architecture is demonstrated.The microwave photonic cognitive radar takes benefits of the broadband operation,real-time processing capability and dynamic reconfigurability of photonics,and can realize high resolution detection and good environment adaptiveness simultaneously.It will provide a clear,reliable,intelligent and all-weather target detection method for automatic drive,security monitoring,space debris management and so on.
作者 潘时龙 朱丹 PAN Shilong;ZHU Dan(Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China)
出处 《雷达科学与技术》 北大核心 2021年第2期117-129,共13页 Radar Science and Technology
基金 国家重点研发计划项目(No.2018YFB2201803) 国家自然科学基金面上项目(No.61971222)。
关键词 稀疏成像 认知技术 频谱侦测 微波光子雷达 sparse imaging cognitive radar spectrum monitoring microwave photonic radars
  • 相关文献

参考文献7

  • 1M.Ablikim,M.N.Achasov,P.Adlarson,S.Ahmed,M.Albrecht,M.Alekseev,A.Amoroso,F.F.An,Q.An,Y.Bai,O.Bakina,R.Baldini Ferroli,Y.Ban,K.Begzsuren,J.V.Bennett,N.Berger,M.Bertani,D.Bettoni,F.Bianchi,J Biernat,J.Bloms,I.Boyko,R.A.Briere,L.Calibbi,H.Cai,X.Cai,A.Calcaterra,G.F.Cao,N.Cao,S.A.Cetin,J.Chai,J.F.Chang,W.L.Chang,J.Charles,G.Chelkov,Chen,G.Chen,H.S.Chen,J.C.Chen,M.L.Chen,S.J.Chen,Y.B.Chen,H.Y.Cheng,W.Cheng,G.Cibinetto,F.Cossio,X.F.Cui,H.L.Dai,J.P.Dai,X.C.Dai,A.Dbeyssi,D.Dedovich,Z.Y.Deng,A.Denig,Denysenko,M.Destefanis,S.Descotes-Genon,F.De Mori,Y.Ding,C.Dong,J.Dong,L.Y.Dong,M.Y.Dong,Z.L.Dou,S.X.Du,S.I.Eidelman,J.Z.Fan,J.Fang,S.S.Fang,Y.Fang,R.Farinelli,L.Fava,F.Feldbauer,G.Felici,C.Q.Feng,M.Fritsch,C.D.Fu,Y.Fu,Q.Gao,X.L.Gao,Y.Gao,Y.Gao,Y.G.Gao,Z.Gao,B.Garillon,I.Garzia,E.M.Gersabeck,A.Gilman,K.Goetzen,L.Gong,W.X.Gong,W.Gradl,M.Greco,L.M.Gu,M.H.Gu,Y.T.Gu,A.Q.Guo,F.K.Guo,L.B.Guo,R.P.Guo,Y.P.Guo,A.Guskov,S.Han,X.Q.Hao,F.A.Harris,K.L.He,F.H.Heinsius,T.Held,Y.K.Heng,Y.R.Hou,Z.L.Hou,H.M.Hu,J.F.Hu,T.Hu,Y.Hu,G.S.Huang,J.S.Huang,X.T.Huang,X.Z.Huang,Z.L.Huang,N.Huesken,T.Hussain,W.Ikegami Andersson,W.Imoehl,M.Irshad,Q.Ji,Q.P.Ji,X.B.Ji,X.L.Ji,H.L.Jiang,X.S.Jiang,X.Y.Jiang,J.B.Jiao,Z.Jiao,D.P.Jin,S.Jin,Y.Jin,T.Johansson,N.Kalantar-Nayestanaki,X.S.Kang,R.Kappert,M.Kavatsyuk,B.C.Ke,I.K.Keshk,T.Khan,A.Khoukaz,P.Kiese,R.Kiuchi,R.Kliemt,L.Koch,O.B.Kolcu,B.Kopf,M.Kuemmel,M.Kuessner,A.Kupsc,M.Kurth,M.G.Kurth,W.Kuhn,J.S.Lange,P.Larin,L.Lavezzi,H.Leithoff,T.Lenz,C.Li,Cheng Li,D.M.Li,F.Li,F.Y.Li,G.Li,H.B.Li,H.J.Li,J.C.Li,J.W.Li,Ke Li,L.K.Li,Lei Li,P.L.Li,P.R.Li,Q.Y.Li,W.D.Li,W.G.Li,X.H.Li,X.L.Li,X.N.Li,X.Q.Li,Z.B.Li,H.Liang,H.Liang,Y.F.Liang,Y.T.Liang,G.R.Liao,L.Z.Liao,J.Libby,C.X.Lin,D.X.Lin,Y.J.Lin,B.Liu,B.J.Liu,C.X.Liu,D.Liu,D.Y.Liu,F.H.Liu,Fang Liu,Feng Liu,H.B.Liu,H.M.Liu,Huanhuan Liu,Huihui Liu,J.B.Liu,J.Y.Liu,K.Y.Liu,Ke Liu,Q.Liu,S.B.Liu,T.Liu,X.Liu,X.Y.Liu,Y.B.Liu,Z.A.Liu,Zhiqing Liu,Y.F.Long,X.C.Lou,H.J.Lu,J.D.Lu,J.G.Lu,Y.Lu,Y.P.Lu,C.L.Luo,M.X.Luo,P.W.Luo,T.Luo,X.L.Luo,S.Lusso,X.R.Lyu,F.C.Ma,H.L.Ma,L.L.Ma,M.M.Ma,Q.M.Ma,X.N.Ma,X.X.Ma,X.Y.Ma,Y.M.Ma,F.E.Maas,M.Maggiora,S.Maldaner,S.Malde,Q.A.Malik,A.Mangoni,Y.J.Mao,Z.P.Mao,S.Marcello,Z.X.Meng,J.G.Messchendorp,G.Mezzadri,J.Min,T.J.Min,R.E.Mitchell,X.H.Mo,Y.J.Mo,C.Morales Morales,N.Yu.Muchnoi,H.Muramatsu,A.Mustafa,S.Nakhoul,Y.Nefedov,F.Nerling,I.B.Nikolaev,Z.Ning,S.Nisar,S.L.Niu,S.L.Olsen,Q.Ouyang,S.Pacetti,Y.Pan,M.Papenbrock,P.Patteri,M.Pelizaeus,H.P.Peng,K.Peters,A.A.Petrov,J.Pettersson,J.L.Ping,R.G.Ping,A.Pitka,R.Poling,V.Prasad,M.Qi,T.Y.Qi,S.Qian,C.F.Qiao,N.Qin,X.P.Qin,X.S.Qin,Z.H.Qin,J.F.Qiu,S.Q.Qu,K.H.Rashid,C.F.Redmer,M.Richter,M.Ripka,A.Rivetti,V.Rodin,M.Rolo,G.Rong,J.L.Rosner,Ch.Rosner,M.Rump,A.Sarantsev,M.Savrie,K.Schoenning,W.Shan,X.Y.Shan,M.Shao,C.P.Shen,P.X.Shen,X.Y.Shen,H.Y.Sheng,X.Shi,X.D Shi,J.J.Song,Q.Q.Song,X.Y.Song,S.Sosio,C.Sowa,S.Spataro,F.F.Sui,G.X.Sun,J.F.Sun,L.Sun,S.S.Sun,X.H.Sun,Y.J.Sun,Y.K Sun,Y.Z.Sun,Z.J.Sun,Z.T.Sun,Y.T Tan,C.J.Tang,G.Y.Tang,X.Tang,V.Thoren,B.Tsednee,I.Uman,B.Wang,B.L.Wang,C.W.Wang,D.Y.Wang,H.H.Wang,K.Wang,L.L.Wang,L.S.Wang,M.Wang,M.Z.Wang,Wang Meng,P.L.Wang,R.M.Wang,W.P.Wang,X.Wang,X.F.Wang,X.L.Wang,Y.Wang,Y.F.Wang,Z.Wang,Z.G.Wang,Z.Y.Wang,Zongyuan Wang,T.Weber,D.H.Wei,P.Weidenkaff,H.W.Wen,S.P.Wen,U.Wiedner,G.Wilkinson,M.Wolke,L.H.Wu,L.J.Wu,Z.Wu,L.Xia,Y.Xia,S.Y.Xiao,Y.J.Xiao,Z.J.Xiao,Y.G.Xie,Y.H.Xie,T.Y.Xing,X.A.Xiong,Q.L.Xiu,G.F.Xu,L.Xu,Q.J.Xu,W.Xu,X.P.Xu,F.Yan,L.Yan,W.B.Yan,W.C.Yan,Y.H.Yan,H.J.Yang,H.X.Yang,L.Yang,R.X.Yang,S.L.Yang,Y.H.Yang,Y.X.Yang,Yifan Yang,Z.Q.Yang,M.Ye,M.H.Ye,J.H.Yin,Z.Y.You,B.X.Yu,C.X.Yu,J.S.Yu,C.Z.Yuan,X.Q.Yuan,Y.Yuan,A.Yuncu,A.A.Zafar,Y.Zeng,B.X.Zhang,B.Y.Zhang,C.C.Zhang,D.H.Zhang,H.H.Zhang,H.Y.Zhang,J.Zhang,J.L.Zhang,J.Q.Zhang,J.W.Zhang,J.Y.Zhang,J.Z.Zhang,K.Zhang,L.Zhang,S.F.Zhang,T.J.Zhang,X.Y.Zhang,Y.Zhang,Y.H.Zhang,Y.T.Zhang,Yang Zhang,Yao Zhang,Yi Zhang,Yu Zhang,Z.H.Zhang,Z.P.Zhang,Z.Q.Zhang,Z.Y.Zhang,G.Zhao,J.W.Zhao,J.Y.Zhao,J.Z.Zhao,Lei Zhao,Ling Zhao,M.G.Zhao,Q.Zhao,S.J.Zhao,T.C.Zhao,Y.B.Zhao,Z.G.Zhao,A.Zhemchugov,B.Zheng,J.P.Zheng,Y.Zheng,Y.H.Zheng,B.Zhong,L.Zhou,L.P.Zhou,Q.Zhou,X.Zhou,X.K.Zhou,Xingyu Zhou,Xiaoyu Zhou,Xu Zhou,A.N.Zhu,J.Zhu,J.Zhu,K.Zhu,K.J.Zhu,S.H.Zhu,W.J.Zhu,X.L.Zhu,Y.C.Zhu,Y.S.Zhu,Z.A.Zhu,J.Zhuang,B.S.Zou,J.H.Zou,无.Future Physics Programme of BESⅢ[J].Chinese Physics C,2020,44(4). 被引量:518
  • 2闫东,张朝霞,赵岩,王娟芬,杨玲珍,施俊鹏.基于信号杂波噪声比的认知雷达扩展目标探测波形设计[J].计算机应用,2015,35(7):2105-2108. 被引量:5
  • 3孙俊.智能化认知雷达中的关键技术[J].现代雷达,2014,36(10):14-19. 被引量:17
  • 4金林.智能化认知雷达综述[J].现代雷达,2013,35(11):6-11. 被引量:30
  • 5代泽洋,王贺,刘宝泉,张春城.认知雷达中协作频谱感知技术研究[J].雷达科学与技术,2015,13(1):17-20. 被引量:5
  • 6XU WANG,FENG ZHOU,DINGSHAN GAO,YANXIAN WEI,XI XIAO,SHAOHUA YU,JIANJI DONG,XINLIANG ZHANG.Wideband adaptive microwave frequency identification using an integrated silicon photonic scanning filter[J].Photonics Research,2019,7(2):172-181. 被引量:3
  • 7Xiaojian Xu,Jia Li.Ultrawide-band radar imagery from multiple incoherent frequency subband measurements[J].Journal of Systems Engineering and Electronics,2011,22(3):398-404. 被引量:7

二级参考文献81

  • 1J. Salzman, D. Akamine, R. Lefevre. Interupted synthetic aperture radar (SAR). Proc. of lEEE National Radar Confer- ence, 2001: 117-122.
  • 2X. Xu, X. B. Feng. SAR/ISAR imagery from gapped data: maximum or minimum entropy? Digest of lEEE AP-S Inter- national Symposium & URSI Meeting, 2005: 122-125.
  • 3X. Xu, R.- Luan, L. Jia, et al. A comparative study of algo- rithms for radar imaging from gapped data. Proc. of SPIE on Unconventional Imaging 111, 2007, 6712: 67120A 1-12.
  • 4J. Tsao, B. D. Steinberg. Reduction of sidelobe and speckle artifacts in microwave imaging: the clean technique. IEEE Trans. on Antennas and Propagation, 1988, 36(4): 543-556.
  • 5R. Bose, A. Freedman, B. D. Steinberg. Sequence CLEAN: a modified deconvolution technique for microwave images of contiguous targets. IEEE Trans. on Aerospace and Electronic Systems, 2002, 38(1): 89-97.
  • 6A. Freedman, R. Bose, B. D. Steinberg. Thinned stepped fre- quency waveforms to furnish existing radar with imaging ca- pability. Proc. of IEEE National Radar Conference, 1996: 65~9.
  • 7Y. Huang, X. Xu. ISAR image reconstruction from periodi- cally gapped data. Digest of lEEE AP S International Sympo- sium & URSI Meeting, 2005: 672-675.
  • 8K. M. Cuomo, J. E. Piou, J. T. Mayhan. Ultrawide-band co- herent processing. IEEE Trans. on Antenna and Propagation, 1999, 47( 6): 1094-1107.
  • 9K. M. Cuomo, J. E. Piou, J. T. Mayhan. Ultra-wideband sensor fusion for BMD discrimination. Proc. of lEEE Radar Conference, 2000: 31-34.
  • 10L. Jia, X. Xu. A new procedure for ultra wideband radar imag- ing from sparse subband data. Proc. of the 8th IEEE Interna- tional Conference on Signal Processing, 2006: 2724-2727.

共引文献572

同被引文献34

引证文献2

二级引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部