Research On 2D DOA Estimation Algorithms

Direction of Arrival(DOA)estimation is one of the research hotspots in the field of signal processing.This thesis aims at the problems of low estimation accuracy,high computational complexity,and the rank loss of covariance matrix caused by coherent signal in two-dimensional DOA estimation algorithm.Based on analysis of the existing algorithms,the following three improvements have been made:1.For the uniform planar array,the Propagator Method(PM)algorithm is improved.The new algorithm is originated in the invariant nature of the uniform planar array translation of the two sub-arrays,and the eigenvalues of its covariance matrix are derived based on the propagator method.The moduli and phase angles of the eigenvalues contain the two-dimensional angular information of the incident signals and the auto-paired two-dimensional angles can be achieved.Compared with the present two-dimensional DOA estimation algorithm based on propagator method,the computational complexity of the new algorithm is significantly reduced while the performance is similar.2.For the uniform circular array,a pattern space-based algorithm is discussed.In this algorithm,the uniform circular array is equivalent to a virtual uniform linear array.The data before and after the equivalent processing contains the same information.The virtual uniform linear array is used to solve the two-dimensional arrival angle estimation of the incident signal.Experiments show that the algorithm effectively reduces the amount of calculations,but the accuracy is too low at high elevation angles.The relationship between the accuracy and various parameters at high elevation angles is analysed.It is proved through experiments that the accuracy can be improved by changing the ratio of the number of uniform circular array elements to the number of virtual uniform linear arrays.3.For the uniform planar array,a covariance matrix reconstruction algorithm is proposed.The algorithm is based on the analysis of the Toeplitz characteristics that sub-blocking matrix of the covariance matrix should meet,but which is no longer satisfied due to the influence of coherent signals.According to the characteristics,the received data vector is used to reconstruct the covariance matrix to meet the requirements.Experiments show that the proposed algorithm can not only improve the array element utilization,but also improve the DOA estimation performance.