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海杂波FRFT域分形特征判别及动目标检测方法

陈小龙 刘宁波 宋杰 关键 何友

陈小龙, 刘宁波, 宋杰, 关键, 何友. 海杂波FRFT域分形特征判别及动目标检测方法[J]. 电子与信息学报, 2011, 33(4): 823-830. doi: 10.3724/SP.J.1146.2010.00486
引用本文: 陈小龙, 刘宁波, 宋杰, 关键, 何友. 海杂波FRFT域分形特征判别及动目标检测方法[J]. 电子与信息学报, 2011, 33(4): 823-830. doi: 10.3724/SP.J.1146.2010.00486
Chen Xiao-Long, Liu Ning-Bo, Song Jie, Guan Jian, He You. Fractal Feature Discriminant of Sea Clutter in FRFT Domain and Moving Target Detection Algorithm[J]. Journal of Electronics & Information Technology, 2011, 33(4): 823-830. doi: 10.3724/SP.J.1146.2010.00486
Citation: Chen Xiao-Long, Liu Ning-Bo, Song Jie, Guan Jian, He You. Fractal Feature Discriminant of Sea Clutter in FRFT Domain and Moving Target Detection Algorithm[J]. Journal of Electronics & Information Technology, 2011, 33(4): 823-830. doi: 10.3724/SP.J.1146.2010.00486

海杂波FRFT域分形特征判别及动目标检测方法

doi: 10.3724/SP.J.1146.2010.00486
基金项目: 

国家自然科学基金(60672140,60802088),航空科学基金(20095184004)和泰山学者建设工程专项经费资助课题

Fractal Feature Discriminant of Sea Clutter in FRFT Domain and Moving Target Detection Algorithm

  • 摘要: 该文研究了海杂波在分数阶Fourier变换(FRFT)域的分形特征,提出了一种基于分形特征差异的联合动目标检测方法。首先,分析了海杂波数据在FRFT域的统计特性,通过对不同极化方式下分形曲线的仿真分析,得到海杂波在FRFT域满足自相似性。其次,给出了分形参数的提取方法和无标度区间,并分析了变换阶数对分形参数估计的影响。最后,利用临近距离单元或临近时刻的雷达回波信号在FRFT域的分形维数和斜距的差值作为检测统计量,经不同极化方式下的海杂波数据验证,表明算法不仅具有良好的微弱动目标检测能力,而且能够准确估计目标的运动状态。
  • Carretero-Moya J, Gismero-Menoyo J, and Asensio-Lpez A, et al.. Application of the Radon transform to detect small- targets in sea clutter[J]. IET Radar, Sonar and Navigation, 2009, 3(2): 155-166.[2] Younsi A, Greco M, Gini F, and Zoubir A M. Performance of the adaptive generalized matched subspace constant false alarm rate detector in non-Gaussian noise: an experimental analysis[J]. IET Radar, Sonar and Navigation, 2009, 3(3): 195-202. [3] Hu J, Tung W W, and Gao J B. 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.[4] Sun Hong-bo, Liu Guo-sui, and Gu Hong. Application of the fractional Fourier transform to moving target detection in airborne SAR[J]. IEEE Transactions on Aerospace and Electronic Systems, 2002, 38(4): 1416-1424.[5] Lv Xiaolei, Xing Meng-dao, and Zhang Shou-hong, et al.. Keystone transformation of the Wigner-Ville distribution for analysis of multicomponent LFM signals[J]. Signal Processing (Elsevier), 2009, 89(5): 791-806.[6] Ltfiye Durak and Orhan Ar-kan. Short-time Fourier transform two fundamental properties and an optimal implementation[J]. IEEE Transactions on Signal Processing, 2003, 51(5): 1231-1242.[7] 张南, 陶然, 王越. 基于变标处理和分数阶傅里叶变换的运动目标检测算法[J]. 电子学报, 2010, 38(3): 683-688.Zhang Nan, Tao Ran, and Wang Yue. A target detection algorithm based on scaling processing and fractional Fourier transform[J]. Acta Electronica Sinica, 2010, 38(3): 683-688.[8] Chen Yang-quan, Sun Rong-tao, and Zhou An-hong. An improved Hurst parameter estimator based on fractional Fourier transform[C]. Proceedings of the ASME 2007 International Design Engineering Technical Conferences Computers and Information in Engineering Conference, Las Vegas, Nevada, USA, 2007: 1-11.[9] 李宝, 关键, 刘宁波. 海杂波FRFT域的分形特性及目标检测[J]. 雷达科学与技术, 2009, 7(3): 210-213.Li Bao, Guan Jian, and Liu Ning-bo. Target detection based on fractal dimension of sea clutter in fractional Fourier transform domain[J]. Radar Science and Technology, 2009, 7(3): 210-213.[10] Drosopoulos A. Description of the OHGR Database[R]. Technology Note No. 94-14, Ottawa: Defence Research Establishment, 1994: 1-30.[11] 姜斌, 王宏强, 黎湘等. S波段雷达实测海杂波混沌分形特性分析[J]. 电子与信息学报, 2007, 29(8): 1809-1812.Jiang Bin, Wang Hong-qiang, and Li Xiang, et al.. The analysis of chaos and fractal characteristic based on the observed sea clutter of S-Band radar[J]. Journal of Electronics Information Technology, 2007, 29(8): 1809-1812.
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出版历程
  • 收稿日期:  2010-05-14
  • 修回日期:  2010-12-16
  • 刊出日期:  2011-04-19

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