Radial neighbor feature with compensate code star pattern recognition algorithm

Yang GAO; Jin-yu ZHAO; Tao CHEN; Min WANG

doi:10.3788/OPE.20172506.1627

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Radial neighbor feature with compensate code star pattern recognition algorithm

Information Sciences | 更新时间：2020-07-07

- Radial neighbor feature with compensate code star pattern recognition algorithm
- Optics and Precision Engineering Vol. 25, Issue 6, Pages: 1627-1634(2017)
- 作者机构：
  
  中国科学院长春光学精密机械与物理研究所, 吉林长春 130033
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20172506.1627
  CLC： TP301.6;V448.2
- Received：28 September 2016，
  
  Accepted：21 November 2016，
  
  Published：25 June 2017
- 稿件说明：
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Yang GAO, Jin-yu ZHAO, Tao CHEN, et al. Radial neighbor feature with compensate code star pattern recognition algorithm[J]. Optics and precision engineering, 2017, 25(6): 1627-1634.
DOI：

Yang GAO, Jin-yu ZHAO, Tao CHEN, et al. Radial neighbor feature with compensate code star pattern recognition algorithm[J]. Optics and precision engineering, 2017, 25(6): 1627-1634. DOI： 10.3788/OPE.20172506.1627.

摘要

针对传统的基于径向特征的星图识别算法在构建星模式的过程中由于位置噪声的干扰导致识别率较低的问题，本文提出一种添加补偿码的快速径向伴星星图识别算法。该算法以比特向量的形式构建基于径向特征的特征向量，同时将伴星间的角距信息以及位置噪声的补偿信息添加到特征向量中，从而有效地减小了特征库的容量，提高了星图识别算法的稳定性和识别率。最后本文根据比特向量的特点采用最小相似差方法快速完成观测星与导航星之间的初匹配，再根据同一视场内星点位置信息的相关性完成对观测星的唯一识别。实验仿真结果表明，在位置噪声为0.5像素的情况下星图识别成功率达到97.8%；在星等噪声为0.8 Mv的情况下星图识别成功率达到96.4%；当以真实星图为实验对象时，星图识别的成功率达到94.2%。与传统的三角形算法以及未添加补偿码的径向特征星图识别算法相比，本文算法在识别成功率和识别时间上均有着不同程度的提高。

Abstract

A fast radial featured star pattern recognition algorithm with compensate code was proposed to solve star model that constructed by traditional radial featured star pattern recognition algorithm could be vulnerable to position noise

lead to low recognition rate. This algorithm adopt byte vector form to construct radial feature vector

meanwhile neighbor angle distance and compensate information were added to feature vector to reduce guide star catalogue capacity and to effectively increase stability and recognition rate of star pattern recognition algorithm. In addition a minimum similar difference matching method was formulated according to the characteristics of byte vector thus completing initial matching between the observation star and the guide star. Fathermore

the characteristic of position information coherency of stars in the same field of view was applied for accomplish exclusive recognition. The result of the experiment shows that recognition rate is 97.8% under position noise of 0.5 pixel

and under magnitude noise of 0.8 Mv is 96.4%. For recognition of real star images

the recognition rate of this algorithm achieves 94.2%. Compared with the triangle algorithm and the traditional radius recognition algorithm

the recognition rate and time of this algorithm are improved in various degrees.

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references

吴量, 王建立, 王昊京.基于最小损失函数的三视场天文定位定向[J].光学精密工程, 2015, 23(3):904-912.

WU L, WANG J L, WANG H J. Three FOVs celestial positioning and orientation with minimum loss function [J]. Opt. Precision Eng., 2015, 23(3):904-912. (in Chinese)

踪华, 汪渤, 周志强, 等.一种基于模式匹配的自主星图识别算法[J].北京理工大学学报, 2015, 35(10):1032-1037.

ZONG H, WANG B, ZHOU Z Q, et al.. An autonomous star identification algorithm based on patterns matching [J]. Transaction of Beijing Institute of Technology, 2015, 35(10):1032-1037. (in Chinese)

毛海岑, 刘爱东, 王亮.采用混合粒子群算法的星图识别方法[J].红外与激光工程, 2014, 43(11):3762-3766.

MAO H C, LIU A D, WANG L. Star recognition method based on hybrid particle swarm optimization algorithm [J]. Infrared and Laser Engineering, 2014, 43(11):3762-3766. (in Chinese)

江洁, 郑佳怡, 凌思睿.新型复合多视场光学敏感器及其导航方法[J].北京航空航天大学学报, 2016, 42(1):1-7.

JIANG J, ZHENG J Y, LING S R.Study of navigation method based on a new multi-field optical sensor [J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(1):1-7. (in Chinese)

张磊, 何昕, 魏仲慧, 等.三角形星图识别算法的改进[J].光学精密工程, 2010, 18(2):458-463.

ZHANG L, HE X, WEI Z H, et al.. Modification of triangle identification algorithm [J]. Opt. Precision Eng., 2010, 18(2):458-463. (in Chinese)

刘先一, 周召发, 张志利, 等.基于数字天顶仪的视场角分析[J].红外与激光工程, 2016, 45(6): 617001-0617001.

LIU X Y, ZHOU Z F, ZHANG Z L, et al.. Analysis of field of view angle based on digital zenith camera [J]. Infrared and Laser Engineering, 2016, 45(6) : 617001-0617001. (in Chinese)

LIEBE C C. Pattern recognition of star constellations for spacecraft applications [J]. IEEE Aeronautics and Electronic Systems Magazine, 1992, 8(1):34-41.

MS Scholl. Star field identification algorithm-Performance verification using simulation star fields[J]. SPIE, 1993, 2019:275-290.

MORTARI D, JUNKINS L J, SAMAAN M A. Lost-in-space pyramid algorithm for robust star pattern recognition[C]. Breckenridge CO:AAS. 2001. http://www.academia.edu/32166836/Lost-in-space_pyramid_algorithm_for_robust_star_pattern_recognition

PADGETT c, KREUTZ-DELGADOK. A grid algorithm for star identification [J]. IEEE Transactions on Aerospace and Electronic Systems 1997, 33(1):202-213.

WEI X G, ZHANG G J, JIANG J. Full-sky autonomous star identification based on radial and cyclic features of star pattern[J]. Image and Vision Computing, 2008, 26(7):891-897.

张少迪, 王延杰, 孙宏海.三角剖分以及径向基函数神经网络在星图识别中的应用[J].光学精密工程, 2012, 20(2):365-402.

ZHANG S D, WANG Y J, SUN H H. Appplication of triangulation and RBF neural network to star pattern recognition [J]. Opt. Precision Eng., 2012, 20(2):365-402. (in Chinese)

唐武盛, 杨建坤, 衣文军, 等.全天自主星图识别网格算法问题分析与改进[J].激光与光电子进展, 2016(2):96-102.

TANG W S, YANG J K, YI W J, et al.. Analysis and improvement of the grid algorithm for autonomous star identification [J].Laser and Optoelectronics Progress, 2016(2):96-102. (in Chinese)

LINDSEY C S, LINDBLAD T. A method for star identification using neural networks [J]. Proc spie, 1997, 3077:471-478.

李超兵, 袁艳艳, 王丹.基于特征图形匹配法的高效星图识别方法[J].中国空间科学技术, 2016, 36(6): 9-16.

LI CH B, YUAN Y Y, WANG D. An efficient stellar map identifivcation method based on characterized graphics matching method [J]. Chineses Space Science and Technology, 2016, 36 (6) : 9-16. (in Chinese)

陈聪, 王宏力, 陆敬辉, 等.基于螺旋基准点的导航星选取方法[J].弹箭与制导学报, 2012, 32 (5):29-32.

CHENG C, WANG H L, LU J H, et al.. Guide star selection method based on spired reference points [J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2012, 32(5): 29-32. (in Chinese)

王凯, 王延杰, 樊博.基于暗通道先验的图像去雾算法改进[J].液晶与显示, 2016, 31(8): 840-845.

WANG K, WANG Y J, FAN B. Improved method for single image dehazing using dark channel prior [J]. Chinese Journal of Liquid Crystals and Displays, 2016, 31(8): 840-845. (in Chinese)

龚昌来, 罗聪.一种改进的容差机制图像去雾算法[J].液晶与显示, 2016, 31(11): 1098-1104.

GONG CH L, LUO C. Improved haze removal algorithm based on tolerance mechanism [J]. Chinese Journal of Liquid Crystals and Displays, 2016, 31(11): 1098-1104. (in Chinese)

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Related Institution

School of Optics and Electronics, Beijing Institute of Technology

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长春理工大学光电工程学院

中国科学院长春光学精密机械与物理研究所, 小卫星技术国家地方联合工程研究中心

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