DOA Estimation Based On Minimum Redundancy Rectangular Array

Direction of Arrival(DOA)estimation of array has a wide range of applications in the fields of electronic warfare and wireless communication.In order to improve the performance of DOA estimation,scholars will study the direction finding algorithm and array structure as a starting point.In terms of array structure,the non-uniform array has a larger aperture and degree of freedom.Under the condition of the same number of array elements,the non-uniform array has better direction finding performance than the uniform array,and the minimum redundancy array has the largest degree of freedom.Compared with the L array and the circular array,the DOA estimation accuracy of the planar array is higher and the estimation performance is stable.Therefore,the minimum redundancy array,which is extended to the planar array,is adopted in this paper.In the aspect of direction finding algorithm,on the one hand,the current algorithms applied to non-uniform arrays are mostly based on spatial smoothing method.This method has a large amount of calculation,which is not conducive to fast DOA estimation.In addition,there are a large number of non-circular signals in the real environment,and its signal characteristics can improve the DOA estimation ability.Therefore,based on the minimum redundancy rectangular array,this paper studies the matrix reconstruction algorithm to reduce the amount of calculation to achieve DOA estimation,and then further extends it to non-circular signal DOA estimation.The main work of this paper is as follows:1.Aiming at the problem that the traditional spatial smoothing method has a large amount of calculation and improves the DOA estimation ability,a DOA matrix reconstruction algorithm based on the minimum redundancy rectangular array is proposed.Firstly,for the problem of large amount of calculation,this paper uses the method of matrix reconstruction to replace the spatial smoothing method to deal with the second-order statistics.The process is to use the second-order statistics to obtain the differential common array of the minimum redundancy rectangular array,and then use the Toeplitz matrix obtained by each uniform linear array in the array.The new covariance matrix is constructed.Compared with the spatial smoothing method,the method of matrix reconstruction in this paper omits the process of calculating the covariance matrix of each sub-array,so the calculation amount is less.At the same time,the new covariance matrix is applied to the two-dimensional MUSIC algorithm and the two-dimensional ESPRIT algorithm and the two-dimensional unitary ESPRIT algorithm;secondly,in order to improve the DOA estimation ability,this paper further applies the matrix reconstruction idea to the fourth-order cumulant,and makes full use of the fourth-order statistics,thus effectively expanding the aperture of the minimum redundant planar array and improving the degree of freedom.These two kinds of algorithms can also be applied to other non-uniform arrays.Finally,the simulation results show that the proposed algorithm has higher accuracy,and under the same algorithm conditions,the DOA estimation performance of the minimum redundancy rectangular array is better than that of the nested planar array,the open box array and the uniform planar array.2.In order to further combine the characteristics of non-circular signals with the matrix reconstruction algorithm to further improve the DOA estimation ability,this paper proposes a DOA estimation algorithm based on non-circular signals and minimum redundancy rectangular array.The elliptic covariance of non-circular signals is not zero.In this paper,this property is used to expand the virtual array of the minimum redundancy rectangular array.There are two ways to expand.The first method is to use the second-order statistics information of noncircular signals for direct vectorization to obtain the sum-difference array,but the sumdifference array has holes.In order to make up for the holes and improve the degree of freedom,this paper obtains the sum-difference array by first array translation and then vectorization,and then combines with the matrix reconstruction algorithm.However,the above method is limited to second-order statistics,so the second method uses non-circular fourth-order cumulants to expand the virtual array and achieve DOA estimation by dimensionality reduction.The final simulation results show that the proposed algorithm has higher accuracy than other non-circular algorithms,and the estimation accuracy of the minimum redundancy rectangular array is higher than that of the coprime rectangular array.