Study On Direction Of Arrival Estimation For Nonlinear Array Based On Sparse Reconstruction

Some limitations exist in traditional Direction of arrival(DOA)estimation methods:angular resolution of the beam-forming technique relies on the amount and inner spacing of array element,which is often called Rayleigh limit;for spatial spectrum estimation,large snapshots are needed to acquire sufficient statistic on covariance matrix of observed signals,this method is sensitive to noise,the performance of this method will be dramatically decreased in low SNR or coherent signals situation.Therefore how to use a small amount of measurement data to achieve high resolution DOA estimation algorithms become an emerging research direction.On the other hand,most of the traditional DOA estimation methods are research on the uniform linear array.But for array systems,the design of the array structure is also a crucial problem,the problem of finding methods to meet the requirements in low system complexity,make the array has more system freedom under the limited number of array element and zhe size of array has been a most important problem for researchers to investigate.In recent years,the developing of the sparse reconstruction theory and the compressed sensing provide a new view for the DOA estimation,It pointed out that the sampled data which is far lower than the Nyquist sampling theorem needed can be used to recover the original signal exactly when the sparse or compressible signals meet certain conditions.Because of the airspace of incoming signal is attribute with sparse structure,the traditional DOA estimation problem can to converted to be a problem of sparse reconstuction.Therefore,it become a hot topic to research the DOA estimation on the sparse reconstuction theory.In terms of array structure,some new array strctures are put forward,which point out the research way for improving the freedom of the array system.The main work of this thesis are listed as follows:1.The related background knowledge of the theory of the DOA estimation algorithms and compressive sensing are summarized.2.Focusing on the three core elements of the theory of compressed sensing emphatically,and then we analyzed the rationality of sparse reconstruction in the DOA estimation.3.This paper discussed and simulation several classic DOA estimation algorithms in detail,including L1-SVD,L1-SRACV,etc,and put forward an improvement measure.4,Several new nonuniform linear array structure are described in detail,including nested array and the co-prime array,etc.The DOA estimation algorithm of these array structure are emulated and analyzed in detail,then we proposed a new algorithm on co-prime array based on the sparse reconstruction.Finally,using a large number of simulation experiments to explain the advantages and disadvantages of the proposed algorithms.