基于联合参数数字信号识别算法的研究

数字信号在敌情监测与侦查、卫星通信、非法电台监测等领域的使用极为广泛,因此对数字信号进行高效地识别、分析和利用具有重要的意义。为了改善信号的抗噪声性能和减小特征参数提取时的计算量,提出了一种利用联合参数对数字信号进行特征参数提取的方法。该方法先利用高阶累积量知识构造出三个参数,再利用信号瞬时幅度构造另外两个参数。最后基于联合参数法,利用神经网络对数字信号进行分类识别。实验结果表明,获取到的参数不仅能有效识别信号,而且当信噪比为10 dB时,识别的正确率可达95%以上,远远优于已有算法。

The research of digital signals recognition based on joint parameters

Digital signals is widely used in many fields, for example, monitoring and investigation of the enemy, satellite communications, illegal radio monitoring and so on. It is significant to identify, analyze and utilize digital signals efficiently. In order to improve the noise immunity of signals and reduce calculations of extracting characteristic parameters, a combined method is proposed for extracting feature parameters. The method firstly uses cumulant knowledge to construct three parameters, then uses instantaneous amplitude to construct other two parameters, based on the combination of characteristic parameters,finally uses neural networks to identify digital signals. The simulation results show that not only the new parameters can effectively identify digital signals in the article, but also the recognition rate over 95% when signal to noise ratio is ten. Compared with the original algorithm, the algorithm is more excellent.