Research Of DOA Estimation Based On The Reduced-Dimensional Algorithm

Direction of arrival(DOA)estimation is one of the important research directions of array signal processing technology.It can obtain the direction information of incoming wave of signal in the spatial domain,which is important for target tracking and locating application.Subspace algorithm is the important theory of super-resolution algorithm on DOA estimation,including the classical algorithm,MUSIC:Multiple Signal Classification,which is widely used because of its simple implementation and high accuracy.In view of the disadvantage of high computational complexity of MUSIC algorithm in near-field signal DOA estimation and two-dimensional array DOA estimation,this thesis studies the MUSIC algorithm based on reduced-dimensional idea,and applies this method to near-field signal DOA estimation and two-dimensional array DOA estimation scenarios,which greatly improves the estimation speed while maintaining the accuracy of DOA estimation.The specific work in this thesis includes:1.Introduce the basic concepts in the field of array signal processing.On this basis,the data models of two-dimensional array DOA estimation and near-field signal DOA estimation are introduced,and the two-dimensional MUSIC algorithm is used for DOA estimation.2.To solve the computational problem of two-dimensional array DOA estimation using MUSIC algorithm,the reduced-dimensional MU SIC algorithm is applied to two-dimensional array DOA estimation.A uniform L-type array signal model is constructed,and two-dimensional angle estimation is achieved by using one-dimensional angle search.MATLAB simulation results show that the algorithm can estimate the two-dimensional angle quickly and accurately.3.In order to solve the problem of computational complexity in near-field signal DOA estimation using MUSIC algorithm,the reduced-dimensional MUSIC algorithm is applied to near-field signal DOA estimation.After constructing the near-field signal model,the near-field angle and the near-field distance are estimated using one-dimensional angle search.MATLAB simulation results show that the algorithm can estimate the near-field angle and distance quickly and accurately.