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微弱高频CW信号的自适应滤波
引用本文:李国军,曾孝平,周晓娜,曾理,蒋勇. 微弱高频CW信号的自适应滤波[J]. 电子科技大学学报(社会科学版), 2010, 0(2)
作者姓名:李国军  曾孝平  周晓娜  曾理  蒋勇
作者单位:重庆大学通信工程学院;中国人民解放军重庆通信学院;
基金项目:国家自然科学基金(60971016);;重庆市教委资助项目
摘    要:高频电报(CW)是强噪声背景下战术应急通信的主要工作方式,由于高频信道是典型的随参信道,不可能事先已知干扰噪声的统计特性。该文提出了一种基于ARMA新息模型的CW信号自适应Kalman滤波方法,以解决高斯背景下高频电报系统干扰噪声方差未知的问题。根据CW信号的时频域特征定义状态空间随机信号模型,构造ARMA新息模型,通过在线辨识新息模型参数来估计Kalman滤波增益,实现CW信号的自适应跟踪滤波。仿真结果表明,该方法能够有效估计微弱高频CW信号时域波形,算法可递推实现,实时性强。

关 键 词:自适应滤波  ARMA新息模型  Kalman滤波  莫尔斯信号  信号检测  

Adaptive Filtering of Weak High-Frequency CW Telegraph Signal
LI Guo-jun,,ZENG Xiao-ping,ZHOU Xiao-na,ZENG Li,, JIANG Yong. Adaptive Filtering of Weak High-Frequency CW Telegraph Signal[J]. Journal of University of Electronic Science and Technology of China(Social Sciences Edition), 2010, 0(2)
Authors:LI Guo-jun    ZENG Xiao-ping  ZHOU Xiao-na  ZENG Li     JIANG Yong
Affiliation:1.College of Communication Engineering;Chongqing Uuniversity Shapingba Chongqing 400044;2.Chongqing Communication Institute Shapingba Chongqing 400035
Abstract:Continuous wave(CW) telegraph is a crucial communication means for high-frequency tactical communication in emergencies.But there exists serious decline in high-frequency channel,thus the statistical properties of interference noise can not be known in advance.A new adaptive Kalman filter based on autoregressive moving average(ARMA) innovation model is proposed in this paper to detect weak high-frequency CW signal with unknown precise statistical variance of Gaussian noise in system.The state space random s...
Keywords:adaptive filtering  ARMA innovation model  Kalman filtering  Morse telegraph signal  signal detection  
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