Sep. 2014

Article Contents

Chinese Optics> 2014> 7(5): 768-778.

WANG Hao-jing, WANG Jian-li, WU Liang, ZHANG Shi-xue, JIA Jian-lu. Fast recognition on star pattern with method of three FOVs based on rough location and azimuth[J]. Chinese Optics, 2014, 7(5): 768-778. doi: 10.3788/CO.20140705.0768

Citation:

WANG Hao-jing, WANG Jian-li, WU Liang, ZHANG Shi-xue, JIA Jian-lu. Fast recognition on star pattern with method of three FOVs based on rough location and azimuth[J].Chinese Optics, 2014, 7(5): 768-778.doi:10.3788/CO.20140705.0768

Citation:

WANG Hao-jing, WANG Jian-li, WU Liang, ZHANG Shi-xue, JIA Jian-lu. Fast recognition on star pattern with method of three FOVs based on rough location and azimuth[J].Chinese Optics, 2014, 7(5): 768-778.doi:10.3788/CO.20140705.0768

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Fast recognition on star pattern with method of three FOVs based on rough location and azimuth

doi:10.3788/CO.20140705.0768

1.
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China;
2.
University of Chinese Academy of Sciences, Beijing 100049, China

Received Date:14 Mar 2014
Rev Recd Date:28 May 2014
Publish Date:25 Sep 2014

Abstract

Abstract

In order to quickly navigate with the known rough azimuth and location information by three FOVs positioning and orientation device, a fast recognition method for local star pattern is proposed. First, we analyse the reasons of the low efficiency when performing the stars identification using global recognition database. Next, we note that it is a preferred method to perform star identification in one FOV firstly and identify the remaining stars between different FVOs, and give the angular distance error threshold. Then, we propose a method to generate the local recognition database, which can reduce the redundancy of identification information and improve recognition efficiency. The simulaion and field experiment results show that the correct identification rate using this recognition method is improved up to 99.19%, and rocognition time is about 24.3 ms, which can satisfy the system requirements for fast and efficient navigation. It also proves the correctness of the preferred recognition order.
- star pattern recognition,
- celestial navigation,
- local star recognition,
- positioning and orientation,
- three fields of view

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References (1)

References

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