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基于分形可变步长LMS算法的海杂波中微弱目标检测

刘宁波 关键 张建

刘宁波, 关键, 张建. 基于分形可变步长LMS算法的海杂波中微弱目标检测[J]. 电子与信息学报, 2010, 32(2): 371-376. doi: 10.3724/SP.J.1146.2009.00017
引用本文: 刘宁波, 关键, 张建. 基于分形可变步长LMS算法的海杂波中微弱目标检测[J]. 电子与信息学报, 2010, 32(2): 371-376. doi: 10.3724/SP.J.1146.2009.00017
Liu Ning-bo, Guan Jian, Zhang Jian. Low-Observable Target Detection in Sea Clutter Based on Fractal-based Variable Step-Size LMS Algorithm[J]. Journal of Electronics & Information Technology, 2010, 32(2): 371-376. doi: 10.3724/SP.J.1146.2009.00017
Citation: Liu Ning-bo, Guan Jian, Zhang Jian. Low-Observable Target Detection in Sea Clutter Based on Fractal-based Variable Step-Size LMS Algorithm[J]. Journal of Electronics & Information Technology, 2010, 32(2): 371-376. doi: 10.3724/SP.J.1146.2009.00017

基于分形可变步长LMS算法的海杂波中微弱目标检测

doi: 10.3724/SP.J.1146.2009.00017

Low-Observable Target Detection in Sea Clutter Based on Fractal-based Variable Step-Size LMS Algorithm

  • 摘要: 该文主要研究了基于Hurst指数与可变步长LMS算法相结合的分析方法在海杂波微弱目标检测中的应用。一直以来,分形理论与统计理论是分别应用到目标检测中的,该文将分形可变步长LMS算法引入到海杂波微弱目标检测中,并在此基础上提出一个海杂波中的微弱目标检测模型,初步实现了基于LMS算法的检测方法与基于单一分形特征的检测方法的结合。最后,采用X波段雷达实测海杂波数据进行验证,结果表明该检测模型具有良好的检测海杂波中微弱目标的能力。
  • Thayaparan T and Kennedy S. Detection of a manoeuvring air target in sea-clutter using joint time-frequency analysis techniques[J].IEE Proceedings-Radar, Sonar and Navigation.2004, 151(1):19-30[2]Davidson G and Griffiths H D. Wavelet detection scheme for small targets in sea clutter[J].Electronics Letters.2002, 38(19):1128-1130[3]Leung H, Dubash N, and Xie N. Detection of small objects in clutter using a GA-RBF neural network[J].IEEE Transactions on Aerospace and Electronic Systems.2002, 38(1):98-118[4]严颂华, 吴世才, 吴雄斌. 基于神经网络的高频地波雷达目标到达角估计[J].电子与信息学报.2008, 30(2):339-342浏览Yan Song-hua, Wu Shi-cai, and Wu Xiong-bin. DOA estimation based on neural network for HFGWR[J].Journal of Electronics Information Technology.2008, 30(2):339-342[5]Lin C P, Sano M, and Sayama S, et al.. Detection of radar targets embedded in sea ice and sea clutter using fractals, wavelets, and neural networks[J]. IEICE Transactions on Communications, 2000, E83-B(9): 1916-1929.[6]田妮莉, 喻莉. 一种基于小波变换和FIR神经网络的广域网网络流量预测模型[J].电子与信息学报.2008, 30(10):2499-2502浏览Tian Ni-li and Yu Li. A WAN network traffic prediction model based on wavelet transform and FIR neural networks[J].Journal of Electronics Information Technology.2008, 30(10):2499-2502[7]Lo T, Leung H, and Haykin S. Fractal characterization of sea-scattered signals and detection of sea-surface targets[J]. IEE Proceedings-F, 1993, 140(4): 243-250.[8]Zhao Min, Fan Yin-hai, and Lv Jin. Chaotic time series gray correlation local forecasting method based on fractal theory[C]. 2007 3rd International Workshop on Signal Design and Its Applications in Communications, 2007: 39-43.[9]Lin C P, Sano M, and Sekine M. Detection of radar targets by means of fractal error[J]. IEICE Transactions on Communications, 1997, E80-B(11): 1741-1748.[10]高远. 海杂波特性分析与基于多重分形理论的目标检测方法研究. [硕士论文], 西安: 电子科技大学, 2007.[11]Gao Yuan. Research on sea clutter characteristic and target detection based on multifractal theory[D]. [MA.dissertation], Xian: Xidian University, 2007.[12]陈双平, 郑浩然, 刘金霞, 等. 离散稳恒信号的多重分形谱的计算及其应用[J].电子与信息学报.2007, 29(5):1054-1057浏览Chen Shuang-ping, Zheng Hao-ran, and Liu Jin-xia, et al.. Computation and applications of multi-fractal to discrete stationary signals[J].Journal of Electronics Information Technology.2007, 29(5):1054-1057[13]Gupta A and Joshi S D. Variable step-size LMS algorithm for fractal signals[J].IEEE Transactions on Signal Processing.2008, 56(4):1411-1419[14]Gupta A and Joshi S D. Characterization of discrete-time fractional brownian motion[C]. IEEE Annual India Conference, New Delhi, India, 2006: 1-6.[15]Drosopoulos A. Description of the OHGR database[R]. Tech. Note No. 94-14, Defence Research Establishment Ottawa, 1994: 1-30.[16]Hu Jing, Tung Wen-Wen, and Gao Jian-bo, et al.. Detection of low observable targets within sea clutter by structure function based multifractal analysis[J].IEEE Transactions on Antennas and Propagation.2006, 54(1):136-143[17]Hsieh Chin-Yuan, Fung A K, and Nesti G, et al.. A further study of the IEM surface scattering model[J].IEEE Transactions on Geoscience and Remote Sensing.1997, 35(4):901-908
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出版历程
  • 收稿日期:  2009-01-08
  • 修回日期:  2009-11-03
  • 刊出日期:  2010-02-19

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