Researches And Implementation Of Broadband Signal Acquisition Based On Compressive Sensing

Because of the limitation of ADC device sampling capability, the traditional informationcollection methods based on Nyquist-Shannon sampling theorem reach a technicalbottleneck when dealing with broadband sparse signal. While sub-Nyquist samplingmethod, which requires lower ADC sampling capability, often need prior spectruminformation of the input analog signal to complete the process of signal reconstructionafter sampling step.Compressive sensing theory rising in recent years has brought new ideas to solve theproblem of broadband sparse signal acquisition. Different from traditional informationgathering process, the information acquisition method based on compressive sensingtheory combine signal sampling step and data compression step into one, not onlyobtain key component of the input signal but also simplify the operation steps. Thesmall amount of data acquired by sampling stage is convenient to transport and storage,furthermore, it’s able to perfectly reconstruct the original by the sampling sequencethrough precise digital algorithm.The information acquisition system discussed in this paper is based on compressivesensing theory, the input signal of system is broadband sparse analog signal which inline with the multi-band model. This information acquisition system is able to handlesignal without any a priori spectral informal, it’s belong to sub-Nyquist blind sampling,and it will be called Compressive Sampling System in this article.The compressive sampling system is composed of signal sampling stage and the signalreconstruction stage. In the sampling stage, the analog input signal which consistentwith the multi-band model first multiply with the high-rate alternating signs waveform,then let the product go through a low-pass filter with appropriate cutoff frequency,finally sample the results far below the Nyquist rate of the original input signal. In thesignal reconstruction stage, whether the support set of original signal can be restoreddetermines the success or failure of the signal reconstruction. After receiving samplingsequences, apply the digital algorithm first to calculate the support set of original signal,and then can easily reconstruct the original analog signal through an analog low-pass filter.This paper first combine compressive sensing theory with project technicalrequirements to construct a signal processing frame, then discuss hardwareimplementing of the theory frame, the frame was divided into Analog parts and Digitalparts by different function, the hardware study discussing in this article is mainly abouthardware design and debug of the Analog parts. It’s mainly contains power supply, inputsignal regulation, signal division, signal mixing, low-pass filtering modules in thehardware design part. Each module in the analog board was taken functional testing,and the result of each module is consistent with expected result of hardware design.