Analysis in Theory and Technology Application of Compressive Sensing

With the information demand increasing, the method which based on Nyquist sampling is expensive and low efficiency in ultra wideband signal processing. To extract before transmission data storage can cause a lot of waste resources. Compressive Sensing can make sampling and compression at the same time. The sampling frequency is far less than the Nyquist sampling frequency as long as the signal is sparse in a domain. It can deal with discrete signal directly and take a few values for processing from n dimension discrete signal. Some algorithm is used to recover on the receiving-end. A compressive Sensing method is proposed in this paper to reduce the requirement of the system in sampling rate. Firstly, the CS basic theory is introduced and three key technologies are summarized: sparse representation of signals, the design of the measurement matrix, compressive sensing reconstruction algorithm. Then the application of compressive sensing technology in specific areas is introduced.