压缩感知理论及其OMP算法FPGA实现研究

Compressed Sensing Theory and OMP Algorithm by FPGA

奈奎斯特定理要求采样频率不得低于信号最高频率的2倍,这使得高频信号的硬件采样实现变得较为困难。压缩感知(Compressive Sensing,CS)理论从研究信号的稀疏性出发,指出在一定条件下可以用低于奈奎斯特定理的频率对信号进行采样。介绍了压缩感知理论及其OMP重构算法,设计了OMP重构算法的FPGA实现的总体框图和各模块框图,编写了Verilog HDL程序代码,并给出了在Quartus II中的仿真结果,和Matlab仿真结果对比,压缩重构效果比较理想。

Nyquist theorem requires that the sampling frequency is not less than 2 times the highest frequency signal,which makes the high-frequency signal sampling hardware implementation and rapid information processing facing enormous challenges. Compressed sensing （CS） theory sampling frequency,based on the sparsity research,under certain conditions,is much lower than the Nyquist theorem.CS theory introduction and it＇s compression reconstruction algorithm is given,and the overall block diagram and the detailed block diagram is designed.