一种新的基于HRRP的雷达目标识别算法

A New Refuse-Recognition Algorithm of Radar Automatic Target Recognition System

雷达目标高分辨距离像(HRRP)包含目标结构信息,是目标重要的分类特征。提出基于独立分量分析(ICA)的雷达目标特征提取方法,将雷达目标高分辨距离像(HRRP)在"基信号"域中分解,提取相应的基系数组成向量,作为目标特征向量。采用反向传播(BP)神经网络作为识别系统的分类器,对神经网络的输出进行编码,为了克服分类器对非库属目标的误判问题,引入拒识门限设计一种新的分类器。采用电磁场时域有限差分(FDTD)算法仿真了飞机的宽带回波,并用所提的方法进行实验。结果表明,基于以上算法的雷达目标识别系统在最大拒识率前提下具有较高的正确识别概率。

Radar high range resolution profile （HRRP） contains target structure information, and RATR based on HRRP has become a hotly researched topic. As high dimension of HRRP, the methpd of independent component analysis （ICA） is proposed to extract some features of HRRP, which is decomposed in the field of ＂base signals＂, and the coefficients are extracted to form vectors as the target＇s feature vectors. The Back -Propagation Network （BP） is employed as the classifier. As the classifier may classify the non - depository target sample, the output of BP network is encoded and the refuse - recognition threshold is proposed in this paper, a new classifier is born when the refuse - recognition threshold is adopted. The classifier can refuse the non - depository target samples and put the depository target samples into its class correctly. The simulation of some targets echoes is done by finite difference time domain （FDTD）. The experiment results show that the method proposed performs well.