Research On DOA Estimation Method Based On Tail Optimization Sparse Recovery

With the complication and diversification of the electromagnetic environment,it is very important that we study the characteristics of the electromagnetic environment.As an important field of electromagnetic sensing,DOA estimation has always been a research hotspot in signal processing.More and more electronic equipment is now being applied to military equipment.If we can accurately grasp the relative position of the target and ours,it is a powerful condition for mastering the initiative of action.Therefore,how to improve the estimation accuracy of DOA estimation algorithm,and reduce the "fakepeak" of spatial spectrum estimation and reduce the error rate of DOA estimation are the biggest challenges faced by researchers.For the traditional spatial spectrum estimation method,it is necessary to collect multiple snapshots to better estimate the DOA problem,and how to use the compressed sensing theory to study DOA.First,the principles and method steps of the traditional method are introduced in this paper.This includes the MUSIC and ESPRIT methods.After simulating two classical methods,we learned about their DOA estimation performance under different conditions.Then we give a commonly used compressed sensing DOA estimation method.It includes the sparse description of the compressed sensing signal and introduces the DOA estimation model under compressed sensing.The RIP sparse criteria and the theoretical framework of compressed sensing are introduced in detail.The performance simulation of l₁-SVD method and OMP method is carried out based on the compressed sensing DOA estimation model.Aiming at improving the accuracy of DOA estimation of the traditional compressed sensing l₁ method,and the solution has multiple "fake-peaks".Using the characteristics of Compressed Sensing with short snapshot and good DOA estimation performance under low SNR,a tail-optimized DOA estimation method based on Compressed Sensing is proposed.This method can effectively remove the "fake-peak" in DOA estimation while improving the DOA estimation accuracy of the traditional compressed sensing l₁ method.In this paper,two kinds of tail optimization methods are proposed.The first one is the tail optimization method whose parameters can be adaptively adjusted under the known number of sources.The other is an l₁-based tail optimization method that does not require a known number of sources.After comparing the performance of the system simulation,the peak of the proposed tail optimization algorithm is sharper and the estimated angle is more accurate.The angle estimation RMSE of the tail optimization method is better than the traditional l₁ method under different snapshot numbers,and the tail optimization algorithm is more stable with the number of snapshots.The tail optimization method can be applied to the field of electronic signal detection and has great theoretical value.It is of great significance to improve the ability of electronic detection and target detection in China.Can improve the angle measurement ability of one station and more stars.It is of great significance to improve the resolving power in electronic detection,radar engineering,communication engineering,measurement and control technology,navigation,sonar,and astronomical array systems.It provides key technical support for the signal processing field of array systems in China and occupies the commanding heights of electronic detection systems.