DOA estimation method suitable for distributed sparse array

Abstract

The invention discloses a DOA estimation method suitable for a distributed sparse array, and belongs to the technical field of DOA estimation algorithms. The problems that an existing DOA estimation algorithm of a distributed sparse array is large in calculation amount, long in operation time and high in hardware performance requirement are solved, signals received by array element antennas of the distributed sparse array are sampled, received signals are obtained, and a covariance matrix of the received signals is calculated; performing vectorization, redundancy elimination and rearrangement processing on the covariance matrix to obtain a receiving signal of the cooperative array, and selecting a receiving signal of a continuous part of the cooperative array as an equivalent receiving signal; constructing a selection matrix according to the dimension of the equivalent received signal; using the selection matrix to select data in the equivalent received signal to construct a Toeplitz matrix; and performing singular value decomposition on the Toeplitz matrix to obtain a feature vector corresponding to the signal subspace, and solving the feature vector corresponding to the signal subspace by adopting a multi-scale ESPRIT algorithm to obtain a DOA estimated value. The method is suitable for DOA estimation.

Description

technical field [0001] The invention belongs to the technical field of DOA estimation algorithm. Background technique [0002] Sparse arrays, such as minimum redundant arrays, coprime arrays, nested arrays, etc., can significantly increase the degree of freedom of the array to increase the maximum number of resolvable source signals. The distributed array has a large baseline length, which effectively increases the aperture of the array and can significantly improve the estimation accuracy of parameters, but it cannot increase the degree of freedom of the array, and the maximum number of source signals to be estimated does not increase. Therefore, the distributed sparse array combines the advantages of the distributed array and the sparse array, which can not only significantly improve the DOA estimation accuracy but also increase the number of maximum resolvable source signals. In DOA estimation of sparse arrays, spatial smoothing is widely used in Multiple Signal Classifi...

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Problems solved by technology

[0003] The purpose of the present invention is to solve the problems of large amount of calculation, long operation time and high requirements on hardware performance in existing DOA estimation algorithms of distributed sparse arrays, and propose a DOA estimation method suitable for distributed sparse arrays

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