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A Star Map Recognition Method Based on Hybrid Particle Swarm Algorithm

A hybrid particle swarm and star map recognition technology, applied in navigation computing tools, astronomical navigation, etc., can solve the problems of slow star map recognition speed and low recognition success rate, reduce redundant matching, improve recognition rate, and ensure real-time sexual effect

Inactive Publication Date: 2016-05-11
BEIHANG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] The purpose of the invention is to solve the problems of slow star map recognition speed and low recognition success rate of star sensor under the condition of large field of view

Method used

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  • A Star Map Recognition Method Based on Hybrid Particle Swarm Algorithm
  • A Star Map Recognition Method Based on Hybrid Particle Swarm Algorithm
  • A Star Map Recognition Method Based on Hybrid Particle Swarm Algorithm

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Embodiment

[0066] When selecting the navigation star and constructing the navigation star catalog, the maximum magnitude of the navigation star is selected as 6.5, and the binary stars whose angular distance between the stars is less than a certain value (take 3 pixels) are eliminated, and the final basic navigation catalog is obtained with a total of 8,996 navigation stars. star. When determining the circle radius r, take the circle radius r = 4°. When the number of star points in the circle takes different values, the number of navigation stars approximately obeys the normal distribution. There are 404 guide stars with less than 6 star points in the circle, greater than 25. There are 628 navigation stars in total, such as figure 2 Shown. When the number of navigation stars in the circle is less than 6, increase the circle radius r to 5°, and the distribution of navigation stars with different numbers of stars in the circle is as follows image 3 As shown; when the number of navigation ...

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Abstract

The invention discloses a hybrid particle swarm algorithm-based star graph recognition method, which comprises two steps of: establishing a navigation star database and performing star graph recognition based on a hybrid particle swarm algorithm, wherein the radius r of a circle is determined through an adaptive adjustment method, and quick path optimization is performed by using the hybrid particle swarm algorithm. According to the hybrid particle swarm algorithm-based star graph recognition method provided by the invention, the defects of low star graph recognition rate and poor noise robustness under conditions of a large visual field and a high-sensitivity fixed star sensor are overcome; and quick matching recognition of a navigation star is realized, the recognition rate is increased, and the noise robustness is better.

Description

Technical field [0001] The invention relates to a star map recognition method based on a hybrid particle swarm algorithm, which belongs to the field of spacecraft navigation, guidance and control. Background technique [0002] The star sensor is the main working component of the celestial navigation system based on the star pattern matching and recognition technology. The star pattern matching and recognition method is the core of the star sensor technology, which can quickly and accurately obtain the attitude information of the carrier. Therefore, studying a star pattern recognition algorithm with fast recognition speed and high recognition success rate has important theoretical and practical significance. [0003] There are many mature star pattern matching and recognition methods, such as triangle algorithm, convex polygon matching recognition algorithm, grid algorithm, Delaunay triangulation recognition method, neural network-based star pattern recognition algorithm, and geneti...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01C21/02G01C21/20
Inventor 杨静王亮
Owner BEIHANG UNIV
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