摘要
海杂波成因复杂多样,并且目标回波受多种因素影响,使得海杂波对于海上目标探测、识别、跟踪产生了严重的影响。针对传统研究方法精度不足的问题,通过分析海杂波相关统计特性,以海杂波幅度特征和基本统计量为基础,构建了以幅度熵、赫斯特指数、频域峰均比为特征分量的三维特征向量,采用卷积神经网络方法,实现海杂波与目标在特征空间中的明显区分。
The causes of sea clutter are complex and diverse,and the target echo is influenced by various factors,which seriously affects the detection,recognition,and tracking of sea targets.In order to solve the problem of insufficient accuracy of traditional research methods,this paper analyzes the statistical characteristics of sea clutter,constructs a three-dimensional feature vector with amplitude entropy,Hurst index and frequency domain peak as the characteristic components,and adopts convolutional neural network method to realize the obvious distinction between sea clutter and targets in feature space.
作者
薛冰
吴巍
Xue Bing;Wu Wei(Naval University of Engineering,Wuhan 430033,China)
出处
《电子技术应用》
2023年第11期15-22,共8页
Application of Electronic Technique
基金
国家自然科学基金(62073334)。
关键词
海杂波
特征向量
卷积神经网络
鉴别精度
sea clutter
feature vector
convolutional neural network
identification accuracy