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改进的分形检测海面漂浮小目标方法
引用本文:刘允峰,索继东,柳晓鸣.改进的分形检测海面漂浮小目标方法[J].电讯技术,2016,56(9):976-981.
作者姓名:刘允峰  索继东  柳晓鸣
作者单位:大连海事大学 信息科学技术学院,辽宁 大连,116026
基金项目:国家高技术研究发展计划(863计划)项目(2012BAH36B02 )
摘    要:为了提高海杂波中漂浮小目标的检测概率,提出了一种改进的分形检测海面漂浮小目标方法。首先,利用去趋势波动分析方法计算海杂波的分形维数;其次,利用计算过程中的“副产品”———截距组成二维判决空间;最后,通过聚类分析,检测出海杂波中的漂浮小目标。在实测数据基础上对改进算法进行了验证,结果表明:海杂波和小目标在判决空间存在明显的差异性;与Hurst指数法、神经网络集成预测法等方法比较,改进算法提高了目标检测概率;交叉极化方式( HV、VH)的检测效果优于同极化方式( HH、VV)的检测效果。

关 键 词:舰载雷达  小目标检测  海杂波  分形维数  截距  去趋势波动分析

An improved fractal approach for detection of weak targets floating on sea clutter
LIU Yunfeng,SUO Jidong and LIU Xiaoming.An improved fractal approach for detection of weak targets floating on sea clutter[J].Telecommunication Engineering,2016,56(9):976-981.
Authors:LIU Yunfeng  SUO Jidong and LIU Xiaoming
Abstract:In order to improve the detection probability of weak targets floating on the sea clutter, an im-proved target detection method based on fractal is proposed. First,fractal dimension of sea clutter is calculat-ed through de-trended fluctuation analysis method. Secondly,two-dimensional decision space is formed with its byproduct———intercept. Finally,small target floating on the sea clutter can be detected through cluster a-nalysis. The improved algorithm is verified by real-live sea clutter data. Experiment results indicate that there are apparent differences between sea clutter and small target in decision space. The improved algorithm can increase the detection probability,compared with the Hurst method,neural network ensemble prediction method and other methods. Detection effect of the cross-polarization( Horizontal-Vertical,Vertical-Horizon-tal) is better than that of the same polarization( Horizontal-Horizontal,Vertical-Vertical) .
Keywords:shipborne radar  weak target detection  sea clutter  fractal dimension  intercept  detrended fluc-tuation analysis
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