摘要
基于实际应用中脉冲流信号的处理面临严峻挑战,压缩感知技术能使信号的采样速率不再取决于信号带宽,而取决于信号中的信息内容,进而获得亚奈奎斯特率采样。因此,可将脉冲流信号进行压缩采样处理,通过构建信号的结构模型,选择合适的测量矩阵,如多通道压缩采样结构中的周期性混频,从而获得更新率采样。多通道压缩采样方法先输入信号与调制波形混频,之后积分并获得信号傅里叶系数的混合样值。未知参数可采用标准谱估计方法从傅里叶系数获得。相对于单通道采样方法,多通道压缩采样结构性能鲁棒,易于电路实现,适于各种脉冲流信号应用。
As to the the serious challenges, the application of pulse stream signal processing is faced, compressed sensing technology can make the signal sampling rate no longer depend on the signal bandwidth, but depend on the signal bandwidth to obtain the sub Nyquist sampling rate. So the pulse stream signal can be sampled and processed, through the structure model of the signal, the appropriate measurement matrix is selected, such as multi-channel periodic mixing compression sampling structure, so as to obtain the innovation rate of sampling. The multi-channel compression sampling method mixes the input signal with the modulation waveform first, then integrates and obtains the mixed sample value of the signal Fourier coefficient. The unknown parameters can be obtained from the Fourier coefficients using standard spectral estimation methods. Compared with the single channel sampling method, the muhi-channel compression sampling structure is robust and easy to implement. It is suitable for various pulse flow signals.
出处
《天津职业技术师范大学学报》
2017年第2期32-36,共5页
Journal of Tianjin University of Technology and Education
基金
天津市自然科学基金资助项目(15JCYBJC52200)
关键词
脉冲流
压缩采样
多通道结构
压缩感知
傅里叶系数
pulse stream
compressed sampling
muhiple channel
compressive sensing
Fourier coefficients