Evolution of compressed sensing theory and dynamic electric energy measurement method

This paper expounds the evolution process of compressed sensing signal sparse model, measurement matrix construction, reconstruction algorithm design, compressed measurement and compressed sensing hardware signal processing system, and puts forward that the future development of compressed sensing theory needs to solve the problems of function sequence processing, including the sparse function sequence signal, the construction of measurement matrix of function sequence signal and CM constraints of measurement matrix, and reduce the complexity of CS hardware system. Aiming at the problems of high complexity and low accuracy of compressed measurement algorithm in the current application of compressed sensing theory, an accurate compressed measurement method of dynamic electric energy value of pseudo-random signal is proposed. The algorithm has low complexity and is easy to implement in hardware. The measurement error of the developed hardware experimental device is better than 2×10-4, which provides a solution strategy to improve the accuracy of compressed detection algorithm, and has the application prospect of high accuracy dynamic electric energy measurement in the future.