基于 Kalman滤波的高频 CW电报信号自动识别
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(1.重庆邮电大学超视距可信信息传输研究所,重庆 400065;2.重庆理工大学计算机科学与工程学院,重庆 400054)

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TN922

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Automatic Recognition of High-Frequency CW Telegraph Signal Based on Kalman Filter
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(1. Beyond Horizon Trusted Communications Institute,Chongqing University of Posts and Telecommunications, Chongqing 400065, China;2. College of Computer Science and Engineering, Chongqing University of Technology, Chongqing 400054, China)

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    摘要:

    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。

    Abstract:

    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.

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引用本文

李国军,乔金亮,周晓娜,叶昌荣.基于 Kalman滤波的高频 CW电报信号自动识别[J].海军航空大学学报,2020,35(1):113-118
LI Guojun, QIAO Jinliang, ZHOU Xiaona, YE Changrong. Automatic Recognition of High-Frequency CW Telegraph Signal Based on Kalman Filter[J]. JOURNAL OF NAVAL AVIATION UNIVERSITY,2020,35(1):113-118

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  • 在线发布日期: 2020-05-06
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