A DOA Estimation Method Based on Partial Mesh Refinement

A direction-of-arrival estimation and grid technology, which is applied in calculation, computer components, design optimization/simulation, etc., can solve the problem of large amount of algorithm calculation, achieve estimation accuracy, reduce computational complexity, and reduce the number of grid points Effect

Active Publication Date: 2022-07-05
GUILIN UNIV OF ELECTRONIC TECH
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Problems solved by technology

The proposal of compressive sensing theory has made a major breakthrough in the DOA estimation problem. Although the DOA estimation algorithm based on the grid model or the out-of-grid model has certain advantages over the traditional algorithm, these sparse signal reconstruction models are based on the spatial angle grid Equally spaced division, in order to pursue estimation accuracy, the grid is densely divided, resulting in a huge amount of algorithm calculation

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  • A DOA Estimation Method Based on Partial Mesh Refinement
  • A DOA Estimation Method Based on Partial Mesh Refinement
  • A DOA Estimation Method Based on Partial Mesh Refinement

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[0026] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to specific examples and accompanying drawings.

[0027] A DOA estimation method based on partial mesh refinement, such as figure 1 As shown, it specifically includes the following steps:

[0028] Step 1: Parameter initialization:

[0029] Based on the initially divided grid points, an off-grid Direction of Arrival (DOA) estimation model for the current observation data is constructed.

[0030] In order to transform DOA estimation into a sparse reconstruction problem, we generally make is the grid points divided at equal intervals in the angle space [-90°, 90°], where N represents the number of grid points.

[0031] For the case of mesh mismatch, the Taylor expansion method is used to calculate the steering vector, namely:

[0032]

[0033] in, represents the distance from θ k near...

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Abstract

The invention discloses a method for estimating the direction of arrival based on grid partial refinement. Through the learning and fission process, the fission process refines the grid by generating new grid points, and the learning process continuously approaches the direction of arrival. The grid near the direction of arrival is subdivided, and the grid area far from the direction of arrival is coarsely divided, which realizes partial refinement of the grid, which not only guarantees the estimation accuracy, but also is in line with the previous off-grid DOA estimation algorithm. The number of grid points is greatly reduced, and the amount of calculation is reduced accordingly. The invention does not need to take the number of sources as a priori, and divides the grid as sparsely as possible, reducing the number of grids, thereby reducing the computational complexity, and the algorithm is less time-consuming; under the condition of very sparse initial grid division, By customizing the minimum interval threshold, the estimation accuracy of the algorithm is guaranteed.

Description

technical field [0001] The invention relates to the technical field of array signal processing, in particular to a method for estimating direction of arrival based on grid partial refinement. Background technique [0002] Direction-of-arrival (DOA) estimation technology is widely used in many fields such as radar, sonar, and meteorology. The most well-known traditional DOA estimation techniques are algorithms such as MUSIC and ESPRIT, but the performance of these traditional algorithms is restricted by many factors, such as high signal-to-noise ratio and large number of snapshots. The proposal of compressive sensing theory has made a major breakthrough in DOA estimation problem. Although DOA estimation algorithms based on grid models and off-grid models have certain advantages over traditional algorithms, these sparse signal reconstruction models are based on spatial angle grids. Equally spaced division, in order to pursue estimation accuracy, the grid is densely divided, r...

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Application Information

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Patent Type & AuthorityPatents(China)
IPC IPC(8): G06F30/23G06K9/62
Inventor蒋留兵荣书伟车俐姜风伟宋占龙周小龙
OwnerGUILIN UNIV OF ELECTRONIC TECH