基于径向基函数的多船舶相互通信信号干扰消除研究  

Research on interference elimination of multi ship communication signals based on radial basis functions

作　　者：吕晓霞 LV Xiaoxia(College of Computer Engineering,Shangqiu University,Shangqiu 476000,China)

机构地区：[1]商丘学院计算机工程学院,河南商丘476000

出　　处：《舰船科学技术》2024年第18期163-166,共4页Ship Science and Technology

摘　　要：为解决多船舶之间的信号干扰,影响通信质量的问题,提出基于径向基函数的多船舶相互通信信号干扰消除方法。设置岸边基站以及海洋中的船舶,分别作为发射机以及接收机。考虑多船舶通信时的直射、海面反射以及大气管道折射路径,构建多船舶相互通信的信道模型,确定多船舶通信信号的特征参数。将所获取的特征参数作为径向基神经网络的输入,利用聚类算法确定隐含层节点中心及径向基函数宽度。引入遗忘因子,利用梯度学习方法训练径向基神经网络,调节隐含层神经元数量及权值。利用完成训练的径向基神经网络,抑制多船舶相互通信信号干扰。实验结果表明,该方法能够有效消除静态干扰以及动态干扰下多船舶通信信号中的干扰成分,降低信号传输误码率。Research on a method for eliminating signal interference in multi ship communication based on radial basis functions,to solve the problem of signal interference between multiple ships and the impact on communication quality.Set up shore base stations and ships in the ocean as transmitters and receivers,respectively.Consider the direct radiation,sea surface reflection,and atmospheric pipeline refraction paths during multi ship communication,construct a channel model for multi ship communication,and determine the characteristic parameters of multi ship communication signals.Using the obtained feature parameters as inputs to the radial basis function neural network,the clustering algorithm is employed to determine the center of the hidden layer nodes and the width of the radial basis function.Introducing forgetting factor and using gradient learning method to train radial basis function neural network,adjusting the number and weights of hidden layer neurons.Utilize the trained radial basis function neural network to suppress signal interference in inter ship communication.The experimental results show that this method can effectively eliminate the interference components in multi ship communication signals under static and dynamic interference,and reduce the signal transmission error rate.

关 键 词：径向基函数 多船舶 相互通信 信号干扰消除 聚类算法 遗忘因子 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]