Electromagnetic vector co-prime area array tensor power spectrum estimation method based on minimization criterion

Abstract

The invention discloses an electromagnetic vector co-prime area array tensor power spectrum estimation method based on a minimization criterion, which mainly solves the problem that the power spectrum estimation precision is limited in the existing method, and comprises the following implementation steps of constructing an electromagnetic vector co-prime area array, conducting tensor modeling of electromagnetic vector co-prime area array receiving signals, performing structured tensor beam forming for the co-prime sparse uniform sub-area array, calculating tensor beam power of the co-prime sparse uniform sub-area array, and conducting electromagnetic vector co-prime area array tensor power spectrum estimation based on sub-area array tensor beam power minimization processing. Based on the spatial filtering principle of electromagnetic vector co-prime area array receiving signal tensor, the correlation between the co-prime layout characteristics and virtual peak distribution characteristics of two sparse uniform sub-area arrays is established, and on the basis, a minimization power processing technology framework based on co-prime sparse uniform sub-area array output signals is formed, therefore, accurate tensor power spectrum estimation is realized, and the method can be used for target positioning and imaging.

Description

technical field [0001] The invention belongs to the field of array signal processing, and in particular relates to a statistical signal processing technology based on electromagnetic vector coprime surface array multi-dimensional receiving signals, specifically a method for estimating the tensor power spectrum of electromagnetic vector coprime surface array based on the minimization criterion, which can be used for Target localization and imaging. Background technique [0002] As a tool to describe the energy distribution of signals in space, power spectrum estimation is widely used in radar, communication, medical imaging, geological exploration and other fields. With the development of science and technology, the requirements for power spectrum estimation performance in increasingly complex application scenarios are also increasing. Compared with traditional uniform arrays, coprime arrays, as a typical sparse array architecture, can break through the limitation of Nyquist...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to solve the problem of limited power spectrum estimation accuracy existing in existing methods, and propose a method for estimating the tensor power spectrum of electromagnetic vector coprime arrays based on the minimization criterion. The signal is associated with the tensor beam power, and the tensor beam power corresponding to the direction of arrival and polarization direction of the signal source is enhanced under the condition of suppressing the virtual peak, so as to realize accurate tensor power spectrum estimation and provide a feasible idea and an effective solution Program

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