Application Method Research On Signal Detection And DOA Estimation Based On Sparse Reconstruction

In modern signal detection theory,the theory of compressed sensing is used to reconstruct the original signal with noise,so as to realize the accurate detection of the target.At the same time,the compressed sensing theory breaks through the limitation of traditional Nyquist sampling frequency,the target signal is sampled at a lower frequency,while maintaining high accuracy,greatly reduce the amount of sampling data,saving storage space.Therefore,compressed sensing theory in estimation of target signal detection and target range(Direction-of-arrival,DOA)has important theoretical significance and application value.Based on this,this paper studies the method of target detection and azimuth estimation which is more suitable for hardware implementation and application.The main contents of this thesis include:An underwater target detection method with low SNR is proposed based on infinite norm reconstruction.The application test,tests show that for low SNR sparse underwater acoustic signal under,through using orthogonal matching pursuit algorithm to reconstruct the infinite norm,can reproduce the main information of the received signal,acoustic detection in low SNR environment,by increasing the number of iterations and reconstruction,can further reduce the minimum detectable signal-to-noise ratio.A fast Laplasse DOA estimation algorithm based on the compressed sensing of the is proposed,which solves the problem of the large amount of iterative computation and the low precision of the algorithm in the reconstruction of the Bias algorithm.With the MUSIC DOA estimation algorithm and convex optimization reconstruction DOA estimation algorithm based on the simulation experiment,the simulation showed that the proposed method has high angular resolution and precision,and can effectively reduce the complexity of the algorithm,thus speeding up the computation time.A method is proposed based on Bayesian estimation ablatival array DOA reconstruction,solve the finite fixed point discrete point error model,and carried out simulation experiments.Simulation results show that the Bayesian in ablative steering vector model under the framework of compressed sensing DOA estimation algorithm can effectively solve the problem of model error of finite fixed point discrete point set,and has a high angular resolution and precision,and can effectively reduce the complexity of the algorithm.