Two-dimensional direction of arrival estimating method based on planar array and estimator

Abstract

The invention relates to a two-dimensional direction of arrival estimating method based on a planar array and an estimator. The two-dimensional direction of arrival estimating method includes the steps that a decoupling model ( F=AL (alpha)*G (beta)+N ) of planar array received signals is built based on the first direction of arrival alpha and the second direction of arrival beta, wherein F represents the planar array received signals, AL (alpha) represents a manifold matrix related to the first direction of arrival alpha, G (beta) represents a signal matrix related to the second direction of arrival beta, and N represents a noise signal matrix; on the premise of alpha domain sparsity, alpha domain sparse reconstruction is carried out on the planar array received signals, so that a support set of alpha domain sparse signals and an alpha estimated value are obtained; on the premise of beta domain sparsity, beta domain sparse reconstruction is carried out on a row vector, corresponding to the alpha estimated value, in the signal matrix G (beta), so that a support set of beta domain sparse signals and a beta estimated value corresponding to the alpha estimated value are obtained. Alpha and beta are sequentially estimated by using the spatial domain sparsity, in an alpha domain and a beta domain, of the incident signals, and therefore computation complexity is reduced substantially.

Description

technical field [0001] This application relates to a two-dimensional DOA estimation method and estimator based on a planar array. Background technique [0002] In the application scenarios of electromagnetic wave signal or acoustic signal processing such as radar, microphone array, etc., it is necessary to analyze the received multi-channel electromagnetic signal or acoustic signal through the antenna array, so as to estimate the direction of arrival (Direction-of-arrival, DOA) of the incident signal . [0003] Existing DOA estimation methods are generally based on one-dimensional direction of arrival DOA estimation, which can be divided into the following four categories: beamforming algorithms, subspace algorithms, maximum likelihood algorithms, and sparse signal reconstruction (SSR) based Methods. Among them, the method based on sparse signal reconstruction imposes sparse constraints on the spatial spectrum, and solves the direction of arrival estimation problem as a sp...

AI Technical Summary

Problems solved by technology

When the method based on sparse signal reconstruction is extended to the two-dimensional direction of arrival estimation problem, the dimension of the redundant dictionary increases sharply, resulting in a sharp increase in computational complexity, which limits the application of the method based on sparse signal reconstruction in actual scenarios

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