Two-dimensional direction finding estimation method based on polynomial rooting in uniform area array

Abstract

The invention discloses a two-dimensional direction-finding estimation method based on polynomial rooting in a uniform area array. The method comprises the following steps: firstly, obtaining a covariance matrix from received signals of the uniform area array; carrying out eigenvalue decomposition on the covariance matrix to obtain a signal subspace and a noise subspace, and determining a rootingpolynomial according to the orthogonal relation between the direction matrix and the noise subspace; finally, solving the root of the polynomial, completing parameter pairing, and completing two-dimensional angle parameter estimation. According to the method, the complexity and the angle estimation performance can be fully balanced, and the limitation that in a traditional two-dimensional angle estimation method, the angle estimation performance is good but the complexity is high or the complexity is low but the angle estimation performance is common is broken through; moreover, high-resolution two-dimensional DOA estimation can be realized, the angle estimation performance is superior to that of a 2D-PM algorithm and a 2D-ESPRIT algorithm, the angle estimation performance is basically consistent with that of a 2D-MUSIC algorithm, and the algorithm complexity is far lower than that of the 2D-MUSIC algorithm.

Description

technical field [0001] The invention belongs to the array signal processing technology, in particular to a two-dimensional direction finding estimation method based on polynomial root finding in a uniform array. Background technique [0002] The early studies on spatial spectrum estimation were all based on uniform linear arrays, but the real signal sources are all in three-dimensional space, and the incident position of the signal source can only be determined by the elevation angle and azimuth angle. Although the uniform linear array has the advantage of simple structure, it is obviously limited to study only one-dimensional DOA estimation, so the research on multi-dimensional parameter estimation has very realistic significance. In recent years, scholars have proposed a variety of joint estimation methods for two-dimensional spatial spectrum estimation and Doppler frequency. Common methods for 2D spatial spectrum estimation mainly include 2D-MUSIC algorithm, 2D-ESPRIT al...

AI Technical Summary

Problems solved by technology

Among them, the 2D-MUSIC algorithm is a typical algorithm for two-dimensional DOA estimation. This method can produce asymptotic unbiased estimation, but it needs to search for spectral peaks in the two-dimensional parameter space, so its computational complexity is very high

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