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海面漂浮小目标的特征联合检测算法 被引量:6

Feature United Detection Algorithm on Floating Small Target of Sea Surface
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摘要 该文研究了高距离分辨海杂波背景下漂浮小目标的检测问题。漂浮目标使得周围海面的散射特性发生了改变,目标所在的分辨单元的回波满足非加性模型,导致该模型中依赖于目标的参数难以统计建模。为了避开参数建模,该文将检测问题转化为二元分类问题,即确定海杂波所属于的类,目标检测就是判别回波是否属于该类。针对此分类问题,提出了基于非加性模型的特征联合检测算法,首先在回波中提取两个特征组成归一化向量,然后利用凸包训练算法获得判别区域,最后以判别区域是否包含该向量作为判别准则。实测的IPIX雷达数据实验结果表明,该文算法在高分辨海杂波下的检测性能优于对比算法,为海事雷达检测小目标提供了新的检测方案。 This paper focus on the detection of floating small targets in high range resolution sea clutter.Floationg targets disarrange the scattering of neighboring sea surface,which results in that the received echoes in the cell targets located satisfy a non-additive model.While,it is hardly to model the paramters correlated to targets in the non-additive model.In order to keep away from the parameter modeling,target detection can be regarded as a binary-classification,where the clutter-only pattern is available for the classifier design and target detection is to judge whether the received echoes belong to the clutter-only pattern.For the classification,a feature united detection algrithm based on the non-additive model is proposed in the paper.First,two extracted features from the received echoes are combined into a normalized vector for target detection.Then,a convex hull training algorithm is utilized to determine a decision region.Finally,the detection rule is whether the decision region surrounds the vector.Experimental results by the raw IPIX radar data show that the proposed algorithm outperforms the compared algorithms.It provides a new detection guidance for the marine radar to detect samll targets.
出处 《电子与信息学报》 EI CSCD 北大核心 2012年第4期871-877,共7页 Journal of Electronics & Information Technology
关键词 目标检测 非加性模型 特征检测 凸包 高距离分辨海杂波 Target detection Non-additive model Feature detection Convex hull High range resolution sea clutter
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  • 1姜斌,王宏强,黎湘,郭桂蓉.海杂波背景下的目标检测新方法[J].物理学报,2006,55(8):3985-3991. 被引量:22
  • 2陈双平,郑浩然,马猛,张振亚,王煦法.用统计物理的方法计算信源熵率[J].电子与信息学报,2007,29(1):129-132. 被引量:3
  • 3Falconer K. Fractal Geometry: Mathematical Foundations and Applications (second edition) [M]. England: John Wiley & Sons, 2003: 3-108.
  • 4Meneveau C and Chhabra A. Two-point statistics of multifractal measures[J]. Physica A, 1990, 164: 564-576.
  • 5O'Neil J and Meneveau C. Spatial correlation in turbulence: Predications from the multifractal formalism and comparison with experiments[J]. Physics Fluids A, 1993, 5(1): 158-172.
  • 6Vapnik V N. The Nature of Statistical Learning Theory[M]. New York: Springer-Verlag, 1995: 5-39.
  • 7Ji Ai-bing, Pang Jia-hong, and Li Shu-huan. Support vector machine for classification based on fuzzy training data[C]. Proceedings of the 5th International Conference on Machine Learning and Cybernetics, Dalian, 2006: 1609-1614.
  • 8ht tp://soma.ece.mcmaster.ca/ipix[EB/OL].
  • 9Hu Jing, Tung Wen-wen, and Gao Jian-bo. 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.
  • 10Sebald D J and Bucklew J A. Support vector machine techniques for nonlinear equalization[J]. IEEE Transactions on Signal Processing, 2000, 48(11): 3217-3226.

共引文献19

同被引文献87

  • 1刘朝军,张欣,王守权.雷达目标恒虚警检测算法研究[J].舰船电子工程,2008,28(7):107-109. 被引量:15
  • 2陈瑛,罗鹏飞.混沌背景下基于RBF神经网络的弱信号检测[J].雷达与对抗,2004,24(2):16-20. 被引量:4
  • 3何伍福,王国宏,刘杰.海杂波环境中基于混沌的目标检测[J].系统工程与电子技术,2005,27(6):1016-1020. 被引量:6
  • 4许小可,柳晓鸣,陈晓楠.基于空间分形特征差异的目标检测[J].大连海事大学学报,2007,33(2):45-48. 被引量:2
  • 5葛德彪,闰玉波.电磁波时域有限差分方法[M].3版.西安:西安电子科技大学出版社,2011.
  • 6Bausssard A, Rochdi M, Khenchaf A. PO/MEC-based scattering model for complex objects on a sea surface [J]. Progress in Electromagnetics Research, 2011, 111 : 229-251.
  • 7Qi c H, Zhao Z Q, Nie Z P. Numerical approach on doppler spectrum analysis for moving targets above a time-evolving sea surface[J]. Progress in Electromagnetics Research, 2013, 138: 351-365.
  • 8Liang Y, Zeng X H, Guo L X, et al. An investigation on numerical characterization of scattering from target in a dielectric rough soil surface[J]. Progress in Electromagneties Research, 2013, 139: 423-444.
  • 9Li J, Wei B, He Q, et al. Time-domain iterative physical optics method for analysis of EM scattering from the target half buried in rough surface: PEC case[J]. Progress in Electromagnetics Research, 2011,121:391-408.
  • 10Sundberg G, Zurk L M, Schecklman S, et al. Modeling rough-surface and granular scattering at terahertz frequencies using the finite-difference time-domain method[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010,48(10): 3709-3719.

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