非合作跳频信号参数的盲压缩感知估计

陈莹 钟菲 郭树旭

陈莹, 钟菲, 郭树旭. 非合作跳频信号参数的盲压缩感知估计[J]. 雷达学报, 2016, 5(5): 531-537. doi: 10.12000/JR15106
引用本文: 陈莹, 钟菲, 郭树旭. 非合作跳频信号参数的盲压缩感知估计[J]. 雷达学报, 2016, 5(5): 531-537. doi: 10.12000/JR15106
Chen Ying, Zhong Fei, Guo Shuxu. Blind Compressed Sensing Parameter Estimation of Non-cooperative Frequency Hopping Signal[J]. Journal of Radars, 2016, 5(5): 531-537. doi: 10.12000/JR15106
Citation: Chen Ying, Zhong Fei, Guo Shuxu. Blind Compressed Sensing Parameter Estimation of Non-cooperative Frequency Hopping Signal[J]. Journal of Radars, 2016, 5(5): 531-537. doi: 10.12000/JR15106

非合作跳频信号参数的盲压缩感知估计

DOI: 10.12000/JR15106
基金项目: 

吉林省教育厅十二五科学研究项目(120150047)

详细信息
    作者简介:

    陈莹(1990-),女,长春人,吉林大学硕士研究生,主要研究方向为非合作信号处理。E-mail:1048390570@qq.com;钟菲(1983-),女,长春人,博士,现为长春工程学院讲师,主要研究方向为信息处理。E-mail:93654872@qq.com;郭树旭(1959-),男,黑龙江人,博士,吉林大学教授,博士生导师,主要研究方向为信号检测与信息处理。E-mail:guosx@jlu.edu.cn

    通讯作者:

    郭树旭guosx@jlu.edu.cn

Blind Compressed Sensing Parameter Estimation of Non-cooperative Frequency Hopping Signal

Funds: 

The 12th Five-Year Plan for Scientific Research Project of Education Department of Jilin Province (120150047)

  • 摘要: 针对非合作跳频通信系统采样速率高,先验信息少等问题,论文提出基于盲压缩感知重构理论参数估计算法。利用稀疏编码与正交基变换交替迭代的思想实现信号精确重构,并根据重构结果直接对跳频信号进行参数估计。与传统的压缩感知理论相比,盲压缩感知理论避免了对信号先验信息的需求,有效解决了非合作通信系统中先验信息少的问题。首先,建立信号模型,然后利用正交块对角盲压缩感知算法(Orthonormal Block Diagonal Blind Compressed Sensing,OBD-BCS)实现信号的重构,并估算出跳变频率及跳变周期。通过实验分析,该方法可以在低信噪比环境下恢复信号原始结构及信息,完成参数估计。

     

  • [1] Wang L, Zhang B, and Zhao Y. Compressive sampling and rapid reconstruction of broadband frequency hopping signals with interference[J]. Circuits, Systems, and Signal Processing, 2015, 34(5):1535-1547.
    [2] Barbarossa S and Scaglione A. Parameter estimation of spread spectrum frequency-hopping signals using time-frequency distributions[C]. First IEEE Signal Processing Working on Signal Processing Advances in Wireless Communications, Paris, 1997:213-216.
    [3] 赵俊, 张朝阳, 赖利峰, 等. 一种基于时频分析的跳频信号参数盲估计方法[J]. 电路与系统学报, 2003, 8(3):46-50. Zhao Jun, Zhang Chao-yang, Lai Li-feng, et al.. Blind parameter estimation of frequency-hopping signals based on time-frequency analysis[J]. Journal of Circuits and Systems, 2003, 8(3):46-50.
    [4] Lv J F, Han Y, and Liang X P. The parameter estimation of non-cooperative frequency hopping signals based on the algorithm of RSPWVD[J]. Applied Mechanics and Materials, 2014, 556/562:4779-4783.
    [5] 郭建涛, 王宏远, 余本海. 基于粒子群算法的跳频信号参数估计[J]. 计算机应用研究, 2010, 27(2):512-514. Guo Jian-tao, Wang Hong-yuan, and Yu Ben-hai. Parameter estimation of frequency hopping signal based on particle swarm optimization[J]. Application Research of Computers, 2010, 27(2):512-514.
    [6] Li B, Li Y, and Zhu Y. Compressive frequency estimation for frequency hopping signal[C]. TENCON 2013-2013 IEEE Region 10 Conference (31194), 2013:1-4.
    [7] 吕晨杰, 王斌, 唐涛. 采用局部特征尺度分解的跳频信号参数盲估计算法[J]. 信号处理, 2015, 31(3):308-313. Lv Chen-jie, Wang Bin, and Tang Tao. Blind parameter estimation of frequency hopping signal using local characteristic-scale decomposition[J]. Journal of Signal Processing, 2015, 31(3):308-313.
    [8] Donoho D L. Compressed sensing[J]. IEEE Transactions on Information Theory, 2006, 52(4):1289-1306.
    [9] Candès E J, Romberg J, and Tao T. Robust uncertainty principles:Exact signal reconstruction from highly incomplete frequency information[J]. IEEE Transactions on Information Theory, 2006, 52(2):489-509.
    [10] Candè E J and Wakin M B. An introduction to compressive sampling[J]. IEEE Magazine Signal Processing, 2008, 25(2):21-30.
    [11] 朱莹, 张弓, 张劲东. 基于DCS的统计MIMO雷达信号模型及参数估计[J]. 雷达学报, 2012, 1(2):143-148. Zhu Ying, Zhang Gong, and Zhang Jin-dong. Signal model and parameters estimation of statistical MIMO radar based on distributed compressed sensing[J]. Journal of Radars, 2012, 1(2):143-148.
    [12] Gleichman S and Eldar Y C. Blind compressed sensing[J]. IEEE Transactions on Information Theory, 2011, 57(10):6958-6975.
    [13] Kreutz-Delgado K, Murray J F, Rao B D, et al.. Dictionary learning algorithms for sparse representation[J]. Neural Computation, 2003, 15(2):349-396.
    [14] Fang B, Huang G, and Gao J. Sub-nyquist sampling and reconstruction model of LFM signals based on blind compressed sensing in FRFT domain[J]. Circuits, Systems, and Signal Processing, 2015, 34(2):419-439.
    [15] 方标, 黄高明, 高俊. LFM宽带雷达信号的盲压缩感知模型[J]. 航空学报, 2014, 35(8):2261-2270. Fang Biao, Huang Gao-ming, and Gao Jun. A blind compressed sensing, model for linear frequency modulated wideband radar signals[J]. Acta Aeronautica et Astronautica Sinica, 2014, 35(8):2261-2270.
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出版历程
  • 收稿日期:  2015-09-21
  • 修回日期:  2016-01-13
  • 网络出版日期:  2016-10-28

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