A Super-Resolution Angle of Arrival Estimation Algorithm Based on Pseudo-Data Reconstruction

Abstract

The invention provides and discloses a super-resolution angle of arrival estimation algorithm based on pseudo-data reconstruction. Construct a covariance matrix with non-divergent noise eigenvalues. When the array steering vector satisfies an odd function, the covariance matrix will be constructed for complex conjugate operation, so that the covariance matrix will contain the DOA information at the symmetrical position of the target, and the covariance matrix will be constructed. Add the constructed covariance matrix after complex conjugate operation to obtain a new covariance matrix. After adding a matching source to the new covariance matrix, the matching covariance matrix is ​​obtained. A new spatial spectrum is constructed by subtracting twice the first eigenvalue corresponding to the noise subspace in the matched covariance matrix and the first eigenvalue corresponding to the noise subspace of the original covariance matrix. The invention improves the angular resolution, which is beneficial to the detection and detection of the target; integrates the symmetrical target information, so that the spectral search range is halved, the algorithm complexity is effectively reduced, and the hardware storage and transmission requirements of the algorithm are reduced.

Description

technical field [0001] The invention relates to an array signal processing method, in particular to a method for estimating the direction of arrival (DOA) of a spatial sound source. Background technique [0002] Ocean as an important strategic link, all countries will pay more attention to ocean research. Sound waves are an indispensable part of ocean exploration. It is the most stable and continuous energy that can propagate in the ocean environment among all forms of energy known so far. The use of sonar to collect sound waves in the ocean and the development of high-resolution and efficient DOA algorithm research will provide a solid theoretical foundation for underwater detection, sonar system development, and shipwreck salvage, which is of great practical significance. [0003] The rise of DOA estimation algorithm can be traced back to traditional beamforming (Conventional Beamformer, CBF), but the spatial spectrum formed by this algorithm has a wide main lobe and larg...

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Problems solved by technology

The literature "Stoica P, Sharman K C. Maximum likelihood methods for direction-of-arrival estimation.[J].IEEE Trans.acoust.speech Signal Process,1990,38(7):1132-1143." once proposed a maximum likelihood Likelihood algorithm (Maximum likelihood methods), this algorithm is a recognized optimal DOA estimator, its performance can approach the Cramer-Rao Lower Bound (CRLB) when the signal-to-noise ratio is large, but this The algorithm needs multi-dimensional nonlinear search to obtain the orientation information, so its complexity will increase exponentially with the increase of the number of parameters, so the algorithm cannot satisfy the increasingly complex actual engineering environment

The literature "Li J, Li D, Jiang D, etal.Extended-Aperture Unitary Root MUSIC-Based DOA Estimation for CoprimeArray[J].IEEE Communications Letters,2018,22(4):752-755." After further research, the unitary transformation Root MUSIC is proposed. This algorithm not only effectively reduces the complexity of the algorithm, but also shows that this algorithm has higher estimation accuracy than conventional MUSIC and Root MUSIC algorithms, but this method reduces the number of identifiable targets. Half, it is only suitable for uniform linear arrays, and the mutual information between arrays will also weaken the DOA estimation performance to a certain extent

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