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基于帧重叠的变速跳频信号分选算法 被引量:2

Variable Speed Hopping Signal Sorting Algorithm Based on Frame Overlap
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摘要 针对当前变速跳频信号采用“跳速多变”策略加大了利用参数估计实现信号分离难度的问题,提出了基于帧重叠的变速跳频信号分选算法。该算法在盲源分离的基础上,通过对变速跳频信号进行重叠帧的构建,利用不同时间帧重叠部分的频率相似性,进行不同时间帧的信号分选,能够解决信号的不确定性问题。仿真结果表明,在信道条件较差时,算法仍可以较为准确地完成不同时间帧信号的分选,得到完整的恢复源信号。 The variable speed hopping signal effectively compensates the shortcomings of the conventional frequency hopping signal by adopting the strategy of continuously increasing the hopping speed and"changing the hopping speed".Aiming at the current research on the sorting algorithm of variable frequency hopping signal and the inherent amplitude and order uncertainty of blind source separation algorithm,an improved variable frequency hopping signal sorting algorithm was proposed.On the basis of blind source separation,the algorithm constructed overlapping frames of variable frequency hopping signals,and used the frequency similarity of overlapping parts of different time frames to perform signal sorting in different time frames.The experimental results showed that the algorithm could still accurately sort the signals of different time frames when the channel conditions were poor,and obtained a complete recovery source signal.
作者 王淼 蔡晓霞 雷迎科 WANG Miao;CAI Xiaoxia;LEI Yingke(College of Electronic countermeasures, National University of Defense Technology, Hefei 230037, China)
出处 《探测与控制学报》 CSCD 北大核心 2020年第4期63-68,共6页 Journal of Detection & Control
关键词 盲源分离 帧重叠 变速跳频信号 blind source separation frame overlap variable frequency hopping signal
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  • 1张朝阳,曹千芊,陈文正.多跳频信号的盲分离与参数盲估计[J].浙江大学学报(工学版),2005,39(4):465-470. 被引量:21
  • 2杨小牛,付卫红.盲源分离——理论、应用与展望[J].通信对抗,2006,25(3):3-10. 被引量:7
  • 3[1]Simon Haykin,Zhe Chen.The Cocktail Party Problem[J].Neural Computation,2005,17:1 875-1 902.
  • 4[3]Adel Belouchrani,Moeness GAmin.Blind Source Separation Based on Time Frequency Signal Representations[ J ].IEEE Transactions on Signal Processing,1998,46 (19):2888-2 897.
  • 5[4]AMARI S,DOUGLAS S,CICHOCKI A.Multichannel blind deconv,olution and equalization using the natural gradient[C].1st IEEE Workshop Signal Processing Adv.Wireless Commun.,Paris,France,1997,4:101-104.
  • 6[3]CARDOSO J F,SOUI OUMIAC.Blind Beamforming for Non-Gaussian Signals[J].Proceedings of IEE F Radar and Signal Processing,1993,140(6):362-370.
  • 7[4]BINGHAM E,HYVARINEN A.A Fast Fixed-point Algorithm for Independent Component Analysis of Complex Valued Signals[J].International Journal of Neural Systems,2000,10(1):1-8.
  • 8[5]CARDOSO J F,DONOHO D L.Equivariant Adaptive Source Separation[J].IEEE Trans.Signal Processing,1996,44(12):3017-3030.
  • 9[6]CARDOSO J F.Blind Signal Separation:Statistical Principles[J].Proceedings of IEEE,1998,86(10):2009-2025.
  • 10[1]Amari S.A theory of adaptive pattern classifiers [J].IEEE Trans.Electronic Computers,1967,16:299-307.

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