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A Star Identification Method Based on Mixed Characteristics and LVQ Neural Network

  • School of Astronautics, Harbin Institute of Technology
  • Beijing Aerospace Automatic Control Institute
  • National Key Laboratory of Science and Technology on Aerospace Intelligence Control

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Star identification method is the basis of celestial navigation. In order to solve the problem that traditional methods can't adapt to high noise condition, a star identification method bases on LVQ neural network is used for star recognition. Compared with several different characteristics vector, the mixed characteristic vector is selected to train the network. The simulation results show that the recognition rate of this star identification method is 100%, and the recognition rate is better than traditional star identification method in high noise condition.

Original languageEnglish
Title of host publication10th International Conference on Modelling, Identification and Control, ICMIC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538654163
DOIs
StatePublished - 9 Nov 2018
Externally publishedYes
Event10th International Conference on Modelling, Identification and Control, ICMIC 2018 - Guiyang, China
Duration: 2 Jul 20184 Jul 2018

Publication series

Name10th International Conference on Modelling, Identification and Control, ICMIC 2018

Conference

Conference10th International Conference on Modelling, Identification and Control, ICMIC 2018
Country/TerritoryChina
CityGuiyang
Period2/07/184/07/18

Keywords

  • LVQ neural network
  • Star Identification
  • Star sensor

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