摘要
甚高频通信在民航中有广泛应用,但是它极易受到各种噪声的干扰,传统方法去噪效果差且没有消除固有干扰,提出了一种基于小波分析的自适应卡尔曼滤波算法。该算法在小波分析中提出了新阈值函数,在自适应卡尔曼滤波算法中增加了调节窗口长度的自适应因子,以此来调节滤波增益,可以有效地避免滤波发散。随机选择了某一时段4种不同频率的甚高频语音信号,并用提出的算法进行滤波处理,从信噪比、均方根误差、信号波形图和语谱图等方面进行分析。结果表明,该算法能够有效去除甚高频语音信号中的噪声,可以获得更高的信噪比和更小的均方根误差,进一步提升语音质量。
VHF communication is widely used in civil aviation, but it is highly susceptible to various noise interferences. The traditional method has poor denoising effect and does not eliminate inherent interference, this paper proposes an adaptive Kalman filter algorithm based on wavelet analysis. In this algorithm, a new threshold function is proposed in the wavelet analysis, and in the adaptive Kalman filter algorithm, an adaptive factor is added to adjust the window length to adjust the filter gain, which can effectively avoid the filter divergence. This paper randomly selects VHF speech signals of four different frequencies in a certain period of time and filtered by the proposed algorithm. The signal-to-noise ratio, root mean square error, signal waveform and spectrogram are analyzed. The results show that the algorithm can effectively remove the noise in VHF speech signal, obtain higher signal-to-noise ratio and smaller root mean square error, and further improve the quality of speech.
作者
卢勇
Lu Yong(Air Traffic Management Center,Civil Aviation Flight University of China,Guanghan 618307,China)
出处
《电子测量技术》
北大核心
2021年第2期65-70,共6页
Electronic Measurement Technology
基金
青年基金项目(Q2019-072)资助。
