基于神经网络的杂波环境判别算法  

Clutter environment discrimination algorithm based on neural network

作　　者：陆赢 周亮 张玉涛 匡华星 LU Ying;ZHOU Liang;ZHANG Yu-tao;KUANG Hua-xing(No.8 Research Academy of CSSC,Nanjing 211153)

机构地区：[1]中国船舶集团有限公司第八研究院,南京211153

出　　处：《雷达与对抗》2022年第3期15-18,共4页Radar & ECM

摘　　要：针对基于帧间幅度判决的杂波环境分类算法缺乏自动能力和杂波误判等不足,提出一种基于神经网络的杂波环境判别算法。考虑到不同环境下雷达回波幅度、相位关系和主通道比等表现不同,将其作为样本的特征信号,通过人工神经网络的非线性处理,将输入的特征信号映射成数个类别的输出,作为环境信息获取的结果,最后通过试验验证了算法的有效性。The clutter environment classification algorithm based on inter-frame amplitude discrimination lacks automation capability and clutter misjudgment.In light of this,a clutter environment discrimination algorithm is proposed based on the neural network.Given that radar echo amplitude,phase relationship and main channel ratio vary in different environments,they are used as the characteristic signals of the sample,and the input characteristic signals are mapped into several categories of outputs through the nonlinear processing of the artificial neural network as the results of environmental information acquisition.The algorithm is verified to be effective through the test.

关 键 词：杂波环境 神经网络 判别 

分 类 号：TN957.51[电子电信—信号与信息处理]