A Coprime Array Underdetermined Direction Finding Method Based on Nullization and Denoising Technology

Abstract

The present invention provides a coprime array underdetermined direction finding method based on zeroization and denoising technology, which specifically includes the following steps: coprime array arrangement and receiving array data; data preprocessing; constructing a uniform virtual array data vector and model noise Covariance matrix; iterative solution to nulling coefficients; equation root finding and direction finding. The advantage of this method compared with the existing technology is: firstly, the estimation of the variance of array noise is introduced in the process of underdetermined solution, and the hole in the virtual array of coprime array is interpolated by using the technology of zeroization and denoising , making full use of all array element information and array degrees of freedom; secondly, the present invention models the model noise caused by the limited number of snapshots, which can improve the accuracy of direction finding; finally, the method proposed by the present invention belongs to the gridless Algorithm, there is no grid effect, and there is no need for spatial grid scanning.

Description

technical field [0001] The invention belongs to the field of array signal processing, and in particular relates to the measurement of incoming wave directions of radar, communication and other electromagnetic waves and acoustic mechanical wave signals, and in particular is a coprime array direction finding method suitable for underdetermined conditions. Background technique [0002] Array direction finding is to use sensor arrays to measure the direction of arrival of signal sources, and is widely used in military and civilian fields such as radar, communication, and sonar. In the past few decades, a large number of excellent direction finding methods have been proposed. However, these methods all have a common problem, that is, they can only perform direction finding on signals whose number is smaller than the number of array elements. When the number of signal sources is greater than or equal to the number of array elements, the traditional method will fail, and we call d...

AI Technical Summary

Problems solved by technology

However, due to the difficulty in estimating the array noise variance under the underdetermined condition, this method discards an array element degree of freedom in order to avoid estimating the array noise variance, resulting in information loss, resulting in a decrease in direction finding performance

Moreover, this method is still a grid algorithm in essence. On the one hand, the grid effect will affect the accuracy of direction finding. On the other hand, it needs to scan the spatial grid to output the direction finding results.

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