Signal Reconstruction And Direction Of Arrival Estimation Based On Compressed Sensing

Compressed sensing is mainly used for projection of sparse or compressible signals.It is widely applied to signal processing field by collecting a small part of the projection value and obtaining the original signal from projection using its corresponding reconstruction algorithm.This thesis mainly uses compression sensing for signal reconstruction and DOA estimation.The main contents of this paper are as follows:(1)The basic principle of compressed sensing is introduced,which includes three aspects: sparse expression of signals,appropriate projection measurement matrix and reasonable reconstruction algorithm.They are described in detail,pointing out the current universal reconstruction algorithm.(2)An orthogonal matching tracking algorithm for particle swarm optimization is proposed,which reconstructs the original signal.As the particle swarm optimization(PSO)algorithm has the characteristics of optimization,the application of PSO to the OMP algorithm can reduce the number of operations to reduce the complexity of the computation.The experiment shows that this method can not only reduce the complexity of calculation,but also improve the probability of successful signal reconstruction.(3)The direction of arrival estimation based on the compression sensing OMP algorithm is proposed.According to the characteristics of the large amount of computation and computing time DOA estimation MUSIC algorithm,OMP algorithm by Schimidt orthogonalization can quickly find a suitable atom,in each iteration,select the corresponding atom matching and residuals optimal DOA value as the estimated value,and greatly shortened the running time.The experiment shows that the method can not only shorten the running time but also reduce the average error,showing obvious superiority.