基于随机解调的模拟信息转换器设计

Design of Analog Information Converter Based on Random Demodulation

压缩感知理论表明,利用信号的稀疏特性可以对信号进行压缩采样,再从少量的观测值中高概率地恢复出原始信号。模拟信息转换器以压缩感知理论为基础,能实现亚奈奎斯特率采样。与传统的模数转换器相比,模拟信息转换器可以有效降低采样速率。提出了一种基于随机解调的模拟信息转换器架构,采用全无源电路实现压缩采样单元。创新性地提出一种全无源的混频电路结构,分两路对被测信号进行随机采样,混频结果经压缩积分网络实现再采样均分运算,从而实现采样信号压缩。压缩采样信号经过量化器得到对应的数字输出编码。实验结果表明,所设计的模拟信息转换器,其峰值信噪比可达到52 dB。

The theory of compressed sensing shows that the sparse characteristics of signals can be used to compress and sample signals,and then the original signals can be recovered from a small number of observations with high probability.Based on compressed sensing theory,the analog information converter can realize sampling with sub-Nyquist rate.Compared with traditional analog-to-digital converters,the analog information converter can effectively reduce the sampling rate.An analog information converter architecture based on random demodulation is proposed in this paper.A completely passive mixing circuit structure is innovatively proposed,which is divided into two channels to randomly sample the measured signals.The mixing results are resampled and equalized by the compression integral network,so as to realize the compression of the sampled signals.The compressed sampled signal is quantized to obtain the corresponding digital output code.The experimental results show that the peak SNR of the analog information converter designed in this paper can reach 52 dB.