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基于EMD和盒维数的固定微弱目标检测 被引量:1

Stationary and Weak Target Detection Based on EMD and Box Dimension
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摘要 为了对强海杂波中的固定微弱目标进行检测,论文提出了基于EMD和盒维数的目标检测算法。该算法首先采用EMD方法在时域内提取海杂波的低频分量,并计算低频分量的盒维数,然后利用盒维数对固定微弱目标进行检测。与仅基于盒维数的微弱目标检测算法相比,该算法扩大了固定目标对海杂波盒维数的影响,明显提高了对固定微弱目标的检测概率。 A new approach based on EMD and box dimension is proposed in this paper to detect the stationary and weak target. Firstly EMD method is used to extract the low frequency component of the sea clutter and the box dimension of the low frequency component is calculated.Then with the box dimension the stationary and weak target is detected.Compared with the approach using the box dimension only,the effect of the stationary and weak target on the box dimension of the sea clutter is greater and the probability of the stationary and weak target detection is much bigger with this approach.
出处 《信号处理》 CSCD 北大核心 2010年第4期492-496,共5页 Journal of Signal Processing
基金 教育部新世纪优秀人才支持计划(NCET-05-0912) 国家自然科学基金资助(60672140 60802088)
关键词 Hilbert-Huang变换(HHT) 盒维数 目标检测 Hilbert-Huang Transformation(HHT) box dimension target detection
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参考文献19

  • 1G. V. Trunk, S. F. George. Detection of targets in non-Gaussian sea clutter [ J ]. IEEE Trans. AES, 1970, 6 (5), pp, 620- 628.
  • 2D. C. SChileher. Radar Detection in Weibull clutter [ J ]. IEEE Trans. AES, 1976, 12(6), pp,736-743.
  • 3E. Jakeman, P. N. Pusey. A model of non-Rayleigh sea echo[ J]. IEEE trans. AP, 1976, 24(6), pp,806-814.
  • 4M. Sekine, T. Musha, Y. Tomita. Log-Weibull Distributed sea clutter[J], lEE Proc. F, 1980, 127(3), pp, 225-228.
  • 5K. D. Ward. Compound representation of high resolution sea clutter[J]. Electronics Letters, 1981, 17 (16), pp, 561- 563.
  • 6S. Haykin and Li X B. Detection of signals in chaos[J]. Proceedings of IEEE. 1995,83( 1 ), pp. 93-122.
  • 7Li X B, S. Haykin. Chaotic detection of small targets in sea clutter[J]. Proc. ICASSP-93. 1993,1, pp. 237-240.
  • 8Leung H and Lo T. Chaotic radar signal processing over the sea [ J ]. IEEE J. Oceanic Engineering. 1993,18 ( 3 ), pp. 287-29.
  • 9Leung H and S. Haykin. Is there a radar clutter attractor [J]. Appl. Phys. Lett,1990,56(6), pp. 593-595.
  • 10He N, S. Haykin. Chaotic modeling of sea clutter[J]. Electronics Letters. 1992,25 ( 10), pp. 2076-2077.

二级参考文献2

  • 1余波.自适应时频方法及其在故障诊断方法中的应用研究[M].大连:大连理工大学,1998..
  • 2马孝江 余伯 张志新.一种新的时频分析方法—局域波法[J].振动工程学报,2000,13(5):219-224.

共引文献45

同被引文献18

  • 1温晓君.海杂波背景下基于神经网络的目标检测[J].系统仿真学报,2007,19(7):1639-1641. 被引量:9
  • 2行鸿彦,徐伟.混沌背景中微弱信号检测的神经网络方法[J].物理学报,2007,56(7):3771-3776. 被引量:37
  • 3Haykin S,Li XB. Detection of signal in chaos[J].{H}Proceedings of IEEE,1995,(01):95-122.
  • 4Haykin S,Deng C. Classification of radar clutter using neural networks[J].{H}IEEE Transactions on Neural Networks,1991,(06):589-600.
  • 5Xie N,Leung H,Chan H. A multiple-model prediction approach for sea clutter modeling[J].{H}IEEE Transactions on Geoscience and Remote Sensing,2003,(06):1491-1502.
  • 6Hennessey G,Leung H,Drosopoulos A,Yip P C. Sea clutter modeling using a radial basis function neural network[J].{H}IEEE Journal of Oceanic Engineering,2001,(03):358-372.
  • 7Harpham C,Dawson C W. The effect of different basis functions on a radial basis function network for time series prediction:A comparative study[J].{H}NEUROCOMPUTING,2006,(16):2161-2170.
  • 8Du H P,Zhang N. Time series prediction using evolving radial basis function networks with new encoding scheme[J].{H}NEUROCOMPUTING,2008.1388-1400.
  • 9关键;刘宁波;黄勇.雷达目标检测的分形理论及应用[M]{H}北京:电子工业出版社,2011.
  • 10Chen YH,Yang B,DongJ W,Abrsham A. Time series forecasting using flexible neural tree model[J].{H}Information Sciences,2005.219-235.

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