Co-prime array underdetermined direction finding method based on zero denoising technology

Abstract

The invention provides a co-prime array underdetermined direction finding method based on a zero denoising technology. The method specifically comprises the following steps of: arranging a co-prime array and receiving array data; preprocessing the data; constructing a uniform virtual array data vector and a model noise covariance matrix; iteratively solving a zeroing coefficient; solving the rootof the equation and measuring the direction. Compared with the prior art, the method has the advantages that firstly, estimation of array noise variance is introduced in the underdetermined solving process, interpolation of holes in a co-prime array virtual array is achieved through adoption of the zeroing denoising technology, and all array element information and the array freedom degree are fully utilized; secondly, modeling is carried out on model noise caused by the limited snapshot number, and the direction finding precision can be improved; finally, the method provided by the inventionbelongs to a meshless algorithm, does not have a grid effect, and does not need to carry out airspace grid scanning.

Description

Technical field [0001] The invention belongs to the field of array signal processing, and particularly relates to the determination of the direction of the electromagnetic wave and acoustic mechanical wave signals such as radar, communication, etc., and in particular is a method of relative prime array direction finding suitable for underdetermined conditions. Background technique [0002] Array direction finding is to use a sensor array to determine the direction of the signal source, which is widely used in military and civilian fields such as radar, communications, and sonar. In the past few decades, people have proposed a large number of excellent direction finding methods. However, these methods all have a common problem, that is, they can only perform direction finding for signals whose number is less 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. We call the 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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