摘要
通信信号调制方式的自动识别在通信对抗领域中具有重要作用,同时也是未来认知无线电系统的重要组成部分,如何在日趋密集的信号环境中快速准确地识别多个混合通信信号是实现通信信号调制方式自动识别的重点。针对这种情况,以数字通信信号的循环谱为特征,通过构建softmax回归多分类识别器,提出一种基于softmax回归的通信信号循环谱的多分类识别方法。通过计算机验证不同条件下的算法性能,证明了该方法无需知道典型的数字调制信号(如ASK,BPSK,QPSK,16QAM,64QAM)的符号率、载频以及同步定时等先验信息,对它们组成的混合信号可以正确识别其中包含的每个调制信号的调制方式,并且识别速度较快。
The automatic identification of communication signal modulation mode has important application in the field of communication countermeasures,and is an important component of the future cognitive radio system,so how to quickly and accurately recognize the multiple mixed communication signals in the increasingly-intensive signal environment is the key to realize the automatic identification of communication signal modulation mode.By taking the cyclic spectrum of the digital communication signals as the feature,and building the softmax regression multi-classification recognizer,a ssoftmax regression based multiclassification recognition method of communication signal cyclic spectrum is put forward.The algorithm performance was verified with computer under different conditions,which proves that the method needn′ t know the symbol rate,carrier frequency,synchronization timing and priori information of the typical digital modulation signals(such as ASK,BPSK,QPSK,16 QAM and64 QAM).The mixed signals can identify the modulation mode including each modulation signal correctly,and has fast identification speed.
出处
《现代电子技术》
北大核心
2018年第3期1-5,共5页
Modern Electronics Technique
基金
国家自然科学基金(61461013)
广西自动检测技术与仪器重点实验室主任基金(YQ15115)
桂林电子科技大学创新团队"广西无线宽带通信与信号处理重点实验室"2016年主任基金项目(GXKL06160103)~~
关键词
softmax
多分类识别
循环谱
调制方式识别
神经网络
电子对抗
softmax
multi-classification recognition
cyclic spectrum
modulation mode recognition
neural network
electronic countermeasure
