Research On Compressive Sampling Technique Of Frequency Hopping And Radar Signal

With the development of information technology,the frequency used in the field of signal processing is getting higher and higher.The sampling technique based on the Nyquist theorem faces some problem such as sampling rate is high,sampling data is redundant and large,and high-speed ADC devices are also difficult to physically implement,so traditional sampling techniques constrain the development of signal processing technology.But the theory of compressed sensing breaks through the limitations of Nyquist's theorem,the AIC technology based on the compression sensing principle can complete the data compression while sampling,effectively solves the problem of high sampling rate and large data volume.In this paper,the AIC techniques based on random demodulation structure and modulation wideband converter are studied,then they are used to sample singals which are sparse in the frequency domain or time domain.The optimization measures for these two compressed sampling structures are also discussed.The main tasks are as follows:(1)The theory of compressed sensing is introduced,several sub-Nyquist sampling techniques are listed,and the advantages of AIC technology based on random demodulation structure or modulated wideband converter are analyzed.(2)The AIC technology based on random demodulation structure or modulated wideband converter is researched and implemented.The principle and technical implementation of the two AIC technologies are described in detail.The function of the two AIC technologies is verified by the signals which is sparse in frequency domain or time domain,and the influence of each parameter in the structure is also analyzed.(3)The function of the modulation signal in in the AIC scheme is analyzed,and the feasibility of reducing the symbol conversion rate of the modulation signal is simulated and analyzed.The measure to reduce the number of channels of the modulated wideband converter is proposed,and the feasibility of the measure is verified by simulation.(4)In order to improve the anti-noise performance of AIC when sampling the signal with frequency domain sparsity,a method which uses the optimized sparse basis to recover the signal is proposed,and the anti-noise performance of the method is also verified by simulation.