[1]王淼,蔡晓霞,雷迎科.改进的欠定变速跳频信号盲分离算法[J].探测与控制学报,2020,42(02):79.[doi:.]
 WANG Miao,CAI Xiaoxia,LEI Yingke.An Improved Blind Separation Algorithm for Underdetermined Variable Speed Frequency Hopping Signals[J].,2020,42(02):79.[doi:.]
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改进的欠定变速跳频信号盲分离算法()
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《探测与控制学报》[ISSN:1008-1194/CN:61-1316/TJ]

卷:
42
期数:
2020年02
页码:
79
栏目:
出版日期:
2020-04-15

文章信息/Info

Title:
An Improved Blind Separation Algorithm for Underdetermined Variable Speed Frequency Hopping Signals
文章编号:
1008-1194(2020)02-0079-07
作者:
王淼蔡晓霞雷迎科
国防科技大学电子对抗学院指挥对抗系,安徽 合肥 230037
Author(s):
WANG Miao CAI Xiaoxia LEI Yingke
Electronic Countermeasure Institute, National University of Defense Technology, Hefei 230037, China
关键词:
欠定盲源分离变速跳频信号“两步法”
Keywords:
underdetermined blind source separation variable speed frequency hopping signal two-step method
分类号:
TN911
DOI:
.
文献标志码:
A
摘要:
针对传统欠定盲源分离算法恢复精度低的问题,提出了改进的欠定变速跳频信号盲分离算法。该算法通过对混合矩阵估计与源信号恢复进行改进,在一定程度上提高了对变速跳频信号盲分离的精确程度。仿真实验表明,恢复信号与源信号相似度在良好信道环境下可以达到90%;在相同条件下,算法的估计误差可以达到约-60 dB。
Abstract:
Aiming at the problem that the traditional underdetermined blind source separation algorithm was of low recovery accuracy, an improved blind separation algorithm for underdetermined variable frequency hopping signals was proposed. The algorithm was improved on the basis of the "two-step method". Simulation experiments showed that the similarity between the recovered signal and the source signal could reach 90% under good channel conditions; under the same conditions, the estimation error of the algorithm could reach about -60 dB.

参考文献/References:

[1]Jutten C,Herault J.Blind separation of sources.part I:an adaptive algorithm based on neuromimetic architecture[J].IEEE Transactions on Signal Processing,1991,24(1):1-10.
[2]Sha Z,Huang Z,Zhou Y.Frequency-hopping signals based on underdetermined blind source separation[J].IET Communications,2013,7(14):1456-1464.
[3]Shen Z, Swary J. Aviyentes S. Underdetermined blind source separation of EEG signals in the time-frequency domain[C]//IEEE Int.Conf on Acoustics Speech and Signal Processing(ICASSP2008).Lasvegas,NVS USA,2008:3637-3640.
[4]付卫红,武少豪,刘乃安.跳频信号的欠定盲源分离[J].北京邮电大学学报,2015,38(6):11-19.
[5]张烨,方勇.基于拉普拉斯势函数的欠定盲分离中源数的估计[J].信号处理,2009,25(11):1719-1725.
[6]ZHANG Chaozhu, WANG Yu, JING Fulong.Underdetermined blind source separation of synchronous orthogonal frequency hopping signals based on single source points detection[J].Sensors, 2017, 17(9):2074-2094.
[7]Wang Jian, Kwon Suhyuk, Li Ping,et al.Recovery of sparse signals via generalized orthogonal matching pursuit:a new analysis[J]. IEEE Transactions on signal processing, 2016,64(4):1076-1089.
[8]陈杰虎. 基于压缩感知的欠定盲分离源信号恢复算法研究[D].西安:西安电子科技大学,2015.
[9]Yang Mingrui, Hoog Frank de.Orthogonal matching pursuit with thresholding and its application in compressive sensing[J]. IEEE Transactions on signal processing. 2015,63(20):5479-5486.
[10]RUAN Guoqing, GUO Qiang, GAO Jingpeng.Novel underdetermined blind source separation algorithm based on compressed sensing and K-SVD[J].Trans Emerging Tel Tech., 2018, 29(9):3427-3440.
[11]Jiang H, Li J, Yi SH,et al. A new hybrid method based on partitioning-based DBSCAN and ant clustering[J].Expert Systems with Applications, 2011, 38(8):9373-9381.
[12]RODRIGUEZ,LAIO.Machine learning clustering by fast search and find of density peaks[J].Science, 2014, 344(6191):1492-1496.

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备注/Memo

备注/Memo:
收稿日期:2019-11-08
作者简介:王淼(1994—),女,新疆乌鲁木齐人,硕士研究生,研究方向:智能信号处理,信号分离。E-mail:wnagmiao18@163.com
更新日期/Last Update: 2020-05-15