强噪声背景下高频CW电报信号的自动检测

长期以来,CW电报通信都靠人工操作来完成,难以满足大容量、高速度的要求,如何实现CW电报的自动检测与识别,减少人为因素的影响,提高其有效性是当前高频CW电报研究的重要课题.在强噪声背景下,高频CW信号的包络检波检测法难以有效跟踪信号波形.检测性能严重下降.针对此问题,提出了一种基于Kalman滤波的微弱CW信号检测方法.该方法首先采用Kalman滤波器实时捕捉CW信号,恢复信号波形,再运用复数谱方差识别干扰信号与CW信号,提取出纯净的CW信号.实验表明:该方法能够在强噪声背景下有效地检测出CW信号,具有更高的识别率,且算法简单,实时性强,可用于指导高频CW电报自动接收设备的研制.

Automatic detection of high-frequency CW telegraph signal in strong noise environment

The sending and reception of CW telegraph have still been completed by operators for a long time. This operation means is difficult to meet the need of large capacity and high speed. Therefore, it is important to implement the automatic detection and recognition of CW telegraph with higher efficiency and less artificial interference. The method of detecting high frequency CW telegraph signal based on envelope demodulation has a poor performance in strong noise environment. Hence, a new method for detecting weak CW signal based on Kalman filtering was presented. Firstly, Kalman filter was applied to resume CW signal, and then pure CW signal was recognized from interfering signal with complex number spectrum variation. Simulation shows that this method is more efficient and simpler in the detection of weak CW signal, and it can be applied to develop automatic receiver of high frequency CW telegraph signal.