Direction of arrival estimation method based on grid partial refinement

Abstract

The invention discloses a direction of arrival estimation method based on grid partial refinement. Through learning and fission processes, in the fission process, new grid points are generated to refine the grid. The learning process is continuously close to the direction of arrival, grids near the real direction of arrival are finely divided, and grid areas far away from the direction of arrivalare coarsely divided, so that partial refinement of the grids is realized, the estimation precision is ensured, and compared with a previous off-grid DOA estimation algorithm, the number of grid points is greatly reduced, and the calculation amount is reduced accordingly. According to the method, the information source number does not need to serve as a priori, grid division is as sparse as possible, the grid number is reduced, therefore, the calculation complexity is reduced, and the algorithm consumes less time. And under the condition of very sparse initial lattice point division, the estimation precision of the algorithm is ensured through minimum interval threshold self-definition.

Description

technical field [0001] The invention relates to the technical field of array signal processing, in particular to a direction-of-arrival estimation method based on grid partial refinement. Background technique [0002] Direction-of-arrival (DOA) estimation technology is widely used in radar, sonar, meteorology and many other fields. Among the traditional DOA estimation techniques, the most well-known algorithms are 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 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 the estimation accuracy, the grid i...

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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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