模型特征映射的开关电容模拟信息转换器设计

A Switch-capacitor Analog-to-information Converter Design Based on Model Feature Mapping

模拟信息转换器(AIC)是模拟数字转换器的替代品,在频域稀疏信号处理中得到了广泛的应用。AIC通过将压缩感知理论从理想的数学计算模型直接映射到物理电路来实现稀疏傅里叶级数系数的测量,同时它引发了模型不匹配的固有问题。提出了一种基于系统状态空间模型系数矩阵的特征值映射的AIC设计方法,为如何从AIC计算模型出发设计电路参数提供了具体的方法。将此方法应用于无源开关电容采样电路,仿真结果表明:重构后的信噪比可达58.8 dB。

Analog to information converter(AIC) is an alternative to the analog-to-digital converter. It is widely used in sparse signal processing in the frequency domain. AIC realizes the measuring of the sparse Fourier series coefficients by directly mapping the compressed sensing theory from the ideal mathematical computing model to the physical circuits. It thereby triggers an inherent problem of model mismatch. In this paper, we propose an AIC design method based on the eigenvalue mapping of the system state space model coefficient matrix. This method provides concrete guidelines on how to design circuit parameters from the AIC computing model. This method is applied in a passive switched-RC sampling circuit. The simulation results demonstrate that the reconstruction signal to noise ratio can reach 58.8 dB.