基于聚类算法的模板匹配信号识别改进算法

Improved algorithm for pattern matching signal recognition based on clustering algorithm

近几十年来,由于无线电通信技术的飞速发展和广泛普及,通信电磁环境越来越复杂,信号和噪声的类别也越来越多,信号的调制识别技术遇到了许多新的挑战。在随机因素的干扰下,通信信号通过提取单一特征进行识别具有一定的不稳定性,因此提出了一种改进的基于聚类算法下的模板匹配算法对信号进行分类研究。该算法采用信息融合的思想,融合4种特征识别6种不同调制类型的通信信号。仿真表明,该算法对多特征信号的分类识别具有较好的应用效果。

In recent decades,because of the rapid development and widespread adoption of radio communication technologies,the electromagnetic environment for communication has become more and more complicated,the types of signals and noise have increased dramatically,and the signal modulation and identification technology has encountered many new challenges.Under the disturbance of random factors,the communication signal has certain instability by extracting a single-feature recognition.Therefore,an improved template matching algorithm based on the clustering algorithm is proposed to identify the signal.The algorithm uses information fusion.The idea incorporates four features to identify six different modulation types of communication signals.The simulation results show that the algorithm has achieved a very good recognition effect on the typical communication signal type recognition.