基于小波降噪的短波通信信号协议识别特征提取算法

利用特征波形匹配来识别短波通信信号协议是简单有效的方法,但易受噪声干扰,影响其有效性.而低信噪比是短波信道特征之一,为此引入小波降噪来构造具有优良抗噪声干扰性能的协议识别特征,以减小噪声对特征波形匹配度的影响.文章提出了一种新的协议识别特征提取算法,该算法通过统计不同信噪比条件下小波系数的波动性,实现了特征波形与待识别信号波形小波系数的合理取舍,并采用取舍后小波系数的匹配度作为识别特征.仿真结果表明,该识别特征能有效减小噪声干扰影响,在低信噪比条件下优势突出.

Protocol Recognition Feature Extraction Algorithm of High Frequency Communication Signals Based on Wavelet De Noising

Characteristic waveform matching is a simple but effective method of protocol recognition of high frequency(HF) communication signals,but its performance is affected by noise interference.Low signal to noise ratio(SNR) is one of the HF channel features,so wavelet de-noising is introduced to depress the noise interference.A novel recognition feature extraction algorithm is proposed to monitor the fluctuation of wavelet coefficients under different SNR conditions and hence set the optimized threshold.With balanced coefficients of characteristic waveform and signal waveform,this algorithm utilizes the matching degree as the recognition feature.Simulation results reveal that this algorithm exhibits excellent performance under low SNR conditions,with noise interference effectively depressed.