摘要
针对非协作通信中的短时突发信号调制方式识别问题,提出了一种基于小波变换的信号相位差统计识别方法,实现了对二相相移键控(BPSK)、四相相移键控(QPSK)、八相相移键控(8PSK)这3种多进制相移键控(MPSK)信号的识别。该方法首先需要估计信号符号速率;然后对希尔比特变换后的待识别信号进行小波变换,提取信号瞬时相位信息并计算其相邻码元相位差序列;最后对相位差信息进行直方图统计,并通过改进的二值削波谱峰搜索算法对其进行峰值搜索,再通过峰值判断输入信号的类型。试验结果表明,在码元数目为150、信噪比大于1 d B时,3种信号调制方式的识别率平均可达96%以上。该算法计算量小,易于工程实现,具有良好的抗频偏性。改进的峰值搜索算法也适用于解决其他各种基于波峰搜索的问题。
Aiming at the issue of modulation recognition of the short burst signalsin non-cooperative communication,a method of signal phase difference statistics recognition based on wavelet transform is proposed to realize recognition for three of multi phase-shift keying signals,i. e.,BPSK,QPSK and 8 PSK. Firstly,it is necessary to estimate the signal symbol rate; then the Hilbert transformed signals which are to be recognized are applied for wavelet transform,to extract the instantaneous signal phase information and calculate its adjacent symbol phase difference sequence; finally,the histogram of the phase difference information is calculated and the peak search is performed by the improved binary clipping peak search algorithm,and the peak number is used to determine the input signal. The experimental results show that when the number of symbols is 150 and the signal noise ratio（ SNR） is more than 1 d B,the recognition rate of the three kinds of signals can reach above 96% on average. The algorithm has the advantages of small amount of calculation,easy to engineering implementation and good capability of anti-frequency deviation. The improved spectral peak search algorithm can also be applied to a variety of other specific problems based on peak search.
出处
《自动化仪表》
CAS
2018年第1期62-65,69,共5页
Process Automation Instrumentation
关键词
突发信号
多进制相移键控(MPSK)
小波变换
调制识别
相位差统计
峰值搜索
Burst signal
Multiple phase shift keying（ MPSK）
Wavelet transform
Modulation recognition
Phase difference statistics
Peak search
