期刊文献+

基于载波相位三差的航天器GPS/INS组合定姿算法 被引量:3

Triple Difference-based Spacecraft GPS/INS Attitude Determination
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摘要 研究了一种利用GPS载波相位三差观测信息的多天线GPS/INS组合定姿算法,其中包含一个基于惯性测量信息的GPS载波相位周跳检测算法。最后,通过仿真分析验证了该组合算法可以有效提高定姿精度,同时具有较好的稳定性。 Based on the triple difference carrier phase observables, a GPS/INS integration algorithm for attitude determination is studied. The proposed integration system also contains a cycle slip detection algorithm, in which inertial information is utilized to detect cycle slip. Some computer simulations are performed to verify the proposed integration system. The results show that accurate and reliable navigation solution can be gained.
机构地区 西北工业大学
出处 《中国空间科学技术》 EI CSCD 北大核心 2006年第4期1-5,10,共6页 Chinese Space Science and Technology
基金 国家自然科学基金资助项目(10402034)
关键词 载波相位 惯性测量 组合算法 全球定位系统 航天器 仿真 Carrier Phase Inertial measurement Combinatorial algorithm Global positioning system Spacecraft Simulation
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参考文献4

  • 1Wolf R, Hein G, Eissfeller B, et al.An Low-cost GPS/INS Attitude Determination and Position Location System.In: ION GPS. Kansas City Missouri, 1996.
  • 2Gebre F. A Low Cost GPS/Inertial Attitude Heading Reference System (AHRS) for tieneral Aviauon Applications. In: IEEE 1998 Position Location and Navigation Symposium-PLANS-1998, Palm Springs, April 20-23, 1998.
  • 3Mathur N G. A New Coning Attitude Algorithm for a Low Cost INS-GPS Integration. Proceedings of ION GPS-1997, Kansas City, Missouri, September 16-19, 1997.
  • 4Jinwon Kim. A Complete GPS/INS Integration Technique Using GPS Carrier Phase Measurements. IEEE PLANS-1998, Palm Springs, April 20-23, 1998.

同被引文献16

  • 1李乡儒,吴福朝,胡占义.均值漂移算法的收敛性[J].软件学报,2005,16(3):365-374. 被引量:89
  • 2谷德峰,易东云,聂鹏程,饶彬.基于样条模型的高精度星间相对定位与定姿[J].宇航学报,2006,27(3):442-447. 被引量:5
  • 3文志强,蔡自兴.Mean Shift算法的收敛性分析[J].软件学报,2007,18(2):205-212. 被引量:47
  • 4BENJAMIN B W, BROWIN G. Triple differencing with Kalman filtering: making it work [ J ]. GPS Solutions, 2000, 3(3) :58-64.
  • 5RIZOS C. Tutorial : Topic 8 : GPS Baseline Processing [ EB/ OL]. [ 2008-10-22]. http://www, groat, unsw. edu. au/ snap/gps/gps_survey/chapS/chap8, htm.
  • 6CHENG Y Z. Mean shift, mode seeking, and clustering [ J]. IEEE Trans on Information Theory, 1975, 21 (1) :32- 40.
  • 7COMANICIU D, MEER P. Mean shift: a robust approach toward feature space analysis [ J ]. IEEE Transaction on Pattern Analysis and Machine Intelligence, 2002, 24 (5) : 603-619.
  • 8MEER P, COMANICIU D. Mean shift analysis and application [ C ]//Proc of the IEEE Intl Conf on Computer Vision (ICCV) Kerkyra, Greece. 1999.
  • 9YANG Changjiang, RAMANI D, LARRY S D. Efficient mean-shift tracking via a new similarity measure [ J ]. CVPR, 2005 ( 1 ) : 176-183.
  • 10王贵文,王泽民,殷海涛.基于三差观测量的实时动态GPS周跳修复方法研究[J].武汉大学学报(信息科学版),2007,32(8):711-714. 被引量:9

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