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基于二维IFS-CFAR算法的海杂波微弱目标检测

Weak Target Detection Based on Two Dimensional IFS-CFAR Algorithm in Sea Clutter
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摘要 一直以来,统计与分形理论是分别应用在目标检测中的;CFAR检测方法采用自适应门限代替固定门限,能根据被检测点的背景噪声、杂波和干扰的大小自适应地调整;文章首先介绍了CFAR恒虚警目标检测方法,给出2D-IFS二维迭代函数系统)预测误差算法;其次运用2D-IFS方法计算了雷达回波的预测误差,结合CA-CFAR统计学目标检测提出一种新的海杂波微弱目标检测方法;最后采用实测海杂波数据进行验证,仿真结果表明文章所提方法对低目标回波信杂比具有良好的检测能力。 For a long time, the statistics and fractal theory are two applied target detection in sea clutter, respectively. The CFAR meth- od can adaptively adjust detection threshold according to the background noise, clutter power or interference power of radar echoes cell when it instead of a fixed threshold. The CFAR cletection method and the 2D-IFS (two--dimensional iterated function systems) are introduced in this article. Next, use the 2D-IFS algorithm to calculate the prediction error of radar echoes, novel weak target detection methods is pro- posed combined with CA-CFAR algorithm. Finally, validated by the real sea clutter data, simulation results show that the proposed method for low SNR (Signal to Noise Ratio) target echo has a good detection capability.
作者 李志海
机构地区 解放军
出处 《计算机测量与控制》 北大核心 2014年第10期3150-3151,共2页 Computer Measurement &Control
关键词 2D-IFS 预测误差 分形自仿射 微弱目标检测 CFAR 2D-IFS algrithm prediction error self-affine fractal CFAR weak target detection
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