Meshless DOA estimation method based on sparse linear array and interpolation virtual transformation technology

Abstract

The invention discloses a meshless DOA (Direction of Arrival) estimation method by combining a sparse linear array with an interpolation virtual transformation technology, which comprises the following steps of: establishing an array signal model of the sparse linear array by a receiving end by adopting array type arrangement of the sparse linear array; calculating according to the array signal model to obtain a first receiving data covariance matrix R of the array; performing interpolation virtual transformation on the first received data covariance matrix R to obtain a virtual covariance matrix, and performing nuclear norm minimization solution on the virtual covariance matrix to obtain an interpolation virtual array covariance matrix T (u); vandermonde decomposition is carried out on the interpolation virtual array covariance matrix T (u) to obtain an estimation frequency F, and a direction-of-arrival estimation value is obtained according to the estimation frequency F. According to the method, the optimization problem is designed based on the idea of interpolation virtual array signal covariance matrix T reconstruction, space grid points do not need to be defined in advance in the optimization problem design process, grid-free direction of arrival estimation is achieved, and meanwhile the resolution and calculation efficiency of direction of arrival estimation are guaranteed.

Description

technical field [0001] The invention belongs to the technical field of signal processing, and in particular relates to a gridless DOA estimation method using a sparse linear array combined with an interpolation virtual transformation technology. Background technique [0002] Facing the needs of accurate estimation of the direction of arrival of radiation sources in complex electromagnetic environments, the sparse aperture array has the advantage of lower complexity compared with the dense array of the same aperture due to the widening of the distance between the array elements. , which has attracted the attention of many scholars. However, due to improper design of the sparse array, it will bring about high spatial side lobes and grating lobes, which will cause the performance of the direction finding method to degrade or even fail completely. Although the traditional gridless DOA estimation method has the advantages that the direction finding accuracy is not affected by th...

AI Technical Summary

Problems solved by technology

In fact the positions of the target signal sources lie in a continuous infinite set of angles, so the assumption only holds when the size of the set tends to infinity, which leads to an unacceptable computational cost

Therefore, the sparse DOA estimation method will inevitably bring estimation bias and affect the estimation performance to a large extent.

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