一种新的模拟到信息转换系统

摘要

目前，模拟到信息转换系统主要通过随机矩阵进行采样的，而用硬件实现随机矩阵是繁杂的，甚至是不可能的。受到压缩传感（Compressive Sensing ，CS ）和积分点火（Integrate-and-Fire ，IF ）电路的启发，本文提出了一种无需随机矩阵且对时域编码的积分式采样还原系统。在稀疏信号足够长的条件下，可以通过参数自由控制采样频率，理论上可以无限降低，大大减少数据量，降低系统功耗。此外它易于实现，无量化误差等优点，在雷达探测、生物传感等宽带信号领域，具有很好的应用前景。%Currently ,analog-to-information conversion system (AIC ) is mainly achieved by random matrix .However ,the hardware implementation of the random matrix is complicated and difficult if not impossible .Inspired by the recent theory of com-pressive sensing (CS ) and integrate-and-fire (IF ) sampler ,we propose a new sampling system which does not contain any random matrix and encodes in the time domain .The output signal sampled by this system can be accurately restored to the original signal . The sampling frequency of the system can be freely controlled if the signal is sparse and the sampling period is sufficiently long . Theoretically ,the sampling frequency can be infinitesimal under those two conditions specified .As a result ,the amount of data and the power consumption of the system can be significantly reduced .In addition ,it is easy to be implemented in practice and has the advantage of no quantization error and so on .The proposed sampling system should have a great potential in applications in the field of broadband signals such as radar signal detection and biological signal measurement .