基于CNN网络算法的无线传感器通信干扰信号识别方法

Recognition Method of Wireless Sensor Communication Interference Signal Based on CNN Network Algorithm

通信干扰信号识别方法通常采用LSTM网络原理设计信号识别算法,这种方法无法深入提取无线传感器通信干扰信号数据之间的内部联系,导致识别率较低。基于此,文章引入CNN卷积神经网络算法原理,提出了一种全新的通信干扰信号识别方法。其针对不同类型的无线传感器通信干扰信号建立模型表达式,获取信号的动态变化,在此基础上,基于CNN网络原理,设计通信干扰信号识别算法,完成干扰信号测试样本的识别。通过实验分析可知,采用本文中提出的方法识别无线传感器通信干扰信号,在信噪比不断变化的情况下,干扰信号识别率较高,均在80%以上,优势显著。

The recognition method of communication interference signals usually adopts the LSTM network principle to design the signal recognition algorithm.This method cannot deeply extract the internal relationship between wireless sensor communication interference signal data,resulting in low recognition rate.Based on this,this paper introduces the principle of CNN convolution neural network algorithm,and proposes a new communication interference signal recognition method.Aiming at different types of wireless sensor communication interference signals,it establishes model expressions to obtain the dynamic changes of signals.On this basis,based on the principle of CNN network,it designs communication interference signal recognition algorithms to complete the identification of interference signal test samples.The experimental analysis shows that the proposed method can identify the interference signal of wireless sensor communication.Under the constant change of SNR,the recognition rate of interference signal is higher,which is more than 80%,with significant advantages.