基于Kalman滤波的高频CW电报信号自动识别

针对强噪声背景下高频CW电报信号检测算法性能严重下降、误码率较高的问题,文章提出一种基于卡尔曼滤波的高频CW电报信号同步检测识别算法。利用自同步法对CW电报信号实现位同步,进而利用卡尔曼滤波针对时变干扰噪声设置自适应阈值,对信号能量进行软判决,实现CW电报信号的自适应跟踪检测,提取有效信号进行识别。通过短波信道仿真软件和实际短波通信测试表明,该算法能够在强噪声背景下有效检测识别CW电报信号,且算法可由迭代实现。

Automatic Recognition of High-Frequency CW Telegraph Signal Based on Kalman Filter

In the background of strong noise, the performance of high-frequency continuous wave(CW) signal detection al?gorithm is seriously degraded and the bit error rate(BER) is high. In this paper, an algorithm based on Kalman filter for de?tection and recognition of CW telegraph signals was proposed. Firstly, the self-synchronization method was used to realizethe bit synchronization of the CW telegraph signal. Then, the Kalman filter was used to set the adaptive threshold for thetime-varying interference noise to make a soft decision on the signal energy, achieve the adaptive tracking detection of theCW telegraph signal, and extract the effective signal for identification. The short-wave channel simulation software and theactual short-wave communication verification show that the proposed algorithm could effectively detect and recognize CWtelegraph signals under strong noise background, and the algorithm was iterative and adaptive.