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

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。

Abstract:

For a long time, the statistics and fractal theory are two applied target detection in sea clutter, respectively. The CFAR method 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 detection 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 proposed 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.