基于小波神经网络的毫米波雷达目标距离像识别

摘要

An artificial neural network with the hidden layer consisting of wavelets was presented for the identification on target profiles of step frequency MMW radar. The good localization characteristics of wavelet functions in both time and frequency space allowed hierarchical multi-resolution learning of input-output data mapping. The mathematic frame of the neural network and error back propagation algorithm were introduced. The procedure of the identification which uses wavelet neural network was described in detail. Then the presented approach was applied to the target profile identification of step frequency MMW radar. The results indicate that the method is valuable for target profile identification.%给出一种隐层由小波基组成的神经网络用于实现频率步进毫米波雷达目标一维距离像的识别.利用小波变换所具有的良好的时频分析特性,实现了输入输出之间映射关系的多分辨学习.介绍了小波神经网络的数学框架及其误差反向学习算法.详细描述了用小波神经网络进行识别的步骤.将所提出的小波神经网络用于频率步进毫米波雷达目标一维距离像的识别.实验结果表明该方法对目标距离像的识别是有效的.