Efficient compressed sensing direction finding method based on special non-uniform linear array

Abstract

The invention belongs to the field of array signal processing, and particularly relates to an efficient compressed sensing direction finding method based on a special non-uniform linear array. Array expansion is carried out using the structure of a special non-uniform linear array, compressed sensing direction finding is carried out on a target in an impact noise environment based on infinite norm, and thus, the optimal estimated value of angle can be obtained. The method is applicable to an impact noise environment, a Gaussian noise environment and a strong impact noise environment, and is suitable for diverse harsh direction finding environments. The infinite norm compressed sensing direction finding method designed can find the direction of a target in an impact noise environment with high accuracy, and can ensure the robustness of direction finding. The special non-uniform linear array designed in the method supports a variety of antenna placement modes without effecting the direction finding performance, and is suitable for more strict requirements on the placement position. Finally, the resolution and the direction finding accuracy of the compressed sensing direction findingmethod are greatly enhanced, and the method has a broader range of applications.

Description

technical field [0001] The invention belongs to the field of array signal processing, and in particular relates to an efficient compressed sensing direction finding method based on a special non-uniform linear array. Background technique [0002] Direction of Arrival (DOA) estimation plays a pivotal role in the field of array signal processing. The rapid development of this technology in the field of military and national economy has brought great changes to array signal processing. Compressed sensing theory can compress and sample the signal at the same time, thus transforming signal samples into information samples. The theory points out that for any sparse or compressible signal in any transform domain, the signal can be sampled with a sampling frequency lower than that of Nyquist, and then the original signal can be sparsely reconstructed by solving an optimization problem. There are only a small amount of interesting signals in the observation space of DOA estimation, ...

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Problems solved by technology

[0003] Compressive sensing DOA estimation has many advantages, but most of the research on this theory is carried out under the condition of uniform linear array (Uniform Linear Array, ULA), as Wang Ying analyzed in the article "Directionestimation using compressive sampling array processing" In the article "Compressed Sensing Direction of Arrival Estimation Based on Non-Uniform Linear Array", Diao Ming designed a method of compressive sensing direction-finding method for non-uniform linear array under Gaussian noise environment. , but there are many problems in this method, such as the ability of the non-uniform linear array to expand the aperture of the array is not strong, it lacks a strict theoretical basis, and it is only effective in a Gaussian noise environment

[0004] When performing direction finding in harsh noise environments such as impact noise, the robustness of direction finding is difficult to guarantee, and the difficulty of direction finding will also increase. Therefore, it is necessary to design high-performance Robust Compressed Sensing Direction Finding Method for

No matter in the environment of Gaussian noise or impact noise, the classical compressed sensing direction finding method is difficult to get rid of the shortcomings of poor convergence accuracy and direction finding failure when the number of antennas is too small, so it is necessary to design a new robust compressed sensing method based on a special non-uniform linear array Direction-finding method, through this method to solve the problem of compressed sensing direction-finding in the impact noise environment, and finally realize that it can also have better performance in harsh noise environments such as impact noise

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