期刊文献+

多敏感器联邦SSUKF融合姿态确定算法 被引量:2

Federated SSUKF for Multi-sensor Spacecraft Attitude Estimation
在线阅读 下载PDF
导出
摘要 针对四元数姿态估计问题,提出了一种分布式非线性滤波融合结构。通过引入基于超球面分布采样点变换(SSUT)技术的无迹卡尔曼滤波算法(SSUKF),以较低的计算量实现了高数据更新率、高精度的非线性滤波,并通过融合重构,保障系统无间断可靠工作,不受敏感器故障、视场盲区等因素影响。应用该算法对陀螺、磁强计、太阳敏感器、星敏感器构成的系统进行了具体设计并开展仿真研究,验证了算法的有效性。 A federated version of spherical simplex unscented Kalman filter ( SSUKF ) was presented for space-borne orbit debris surveillance mission. The nonlinear transformation filtering method brought the algorithm a high precision, while the reduced sigma point filtering technique endowed the algorithm with a high computing speed, and the decentralized structure ensured the algorithm a good capability of reconstruction in case of sensor fault or vision limit. A filtering system composed of gyroscopes, magnetometer, sun sensor and star tracker was designed using this algorithm, and was validated with numerical simulation.
出处 《中国空间科学技术》 EI CSCD 北大核心 2009年第6期21-27,80,共8页 Chinese Space Science and Technology
关键词 姿态确定 超球面分布采样点变换 离散卡尔曼滤波 信息融合 故障诊断 Attitude determination Spherical simplex unscented transformation Federated unscented Kalman filter Fusion Fault detection
  • 相关文献

参考文献15

二级参考文献29

  • 1黄显林,王宇飞,胡恒章.一种基于特征值分解的自适应信息融合滤波算法[J].中国惯性技术学报,1999,7(4):43-45. 被引量:6
  • 2董云峰,章仁为.利用星敏感器的卫星自主导航[J].宇航学报,1995,16(4):36-41. 被引量:19
  • 3俞济祥.卡尔曼滤波及其在惯性导航中的应用[M].北京:航空专业教材编审组,1984..
  • 4Neal A. Carlson. Federated Filter for Computer- Effcient,Near- Optimal GPS Integration, 0 - 7803 - 3085 - 4/96,1996 IEEE.
  • 5Y. Gao and E. J. Krakiwsky. Experience with the Application of Federated Filter Design to Kinematic GPS Positioning,0 - 7803 - 0468 - 3/92, 1992 IEEE.
  • 6J. Chris McMillan: A GPS Attitude Error Model for Kalman Filtering. Defence Research Establshment Ottawa, 1994.
  • 7杨静.[D].北京航空航天大学,加02.4.
  • 8Vasile M,Sironi F,Zazzera F B.Deep space autonomous orbit determination using CCD[R].AIAA-2002-4818,2002
  • 9Bhaskaran S,Riedel J E,Kennedy B,Wang T C.Navigation of the Deep Space 1 spacecraft at Borrelly[R].AIAA-2002-4815,2002
  • 10VanDyke M C,Schwartz J L,Hall C D.Unscented kalman filtering for spacecraft attitude state and parameter estimation[R].AAS-04-115,2004

共引文献81

同被引文献9

  • 1LIU Ye1,YU AnXi1,ZHU JuBo2 & LIANG DianNong1 1 College of Electronic Science and Engineering,National University of Defense Technology,Changsha 410073,China,2 Science College,National University of Defense Technology,Changsha 410073,China.Unscented Kalman filtering in the additive noise case[J].Science China(Technological Sciences),2010,53(4):929-941. 被引量:18
  • 2傅建国,王孝通,金良安,马野.Sigma点卡尔曼滤波及其应用[J].系统工程与电子技术,2005,27(1):141-144. 被引量:17
  • 3Julier S J, Uhlmann J K, Durrant-Whyte H F. A new approach for filtering nonlinear system[C]//Proceedings of the American Control Conference. Seattle, Washington, 1995: 1628-1632.
  • 4Julier S J, Uhlmann J K, Durrant-Whyte H F. A new approach for the nonlinear transformation of means and covariances in filters and estimators[J]. IEEE Transac- tions on Automatic Control, 2000, 45(3): 477-482.
  • 5Zhao Lin, Wang Xiaoyu. An adaptive UKF with noise statistic estimator[C]// IEEE Conf. Ind. Electron. Appl., ICIEA. Xi'an: IEEE Computer Society on Automatic Control, 2009: 614-618.
  • 6Julier S J. The spherical simplex unscented transformation [C]// Proceedings of the American Control Conf. Denver, Colorado, 2003: 2430-2434.
  • 7严恭敏,严卫生,徐德民.简化UKF滤波在SINS大失准角初始对准中的应用[J].中国惯性技术学报,2008,16(3):253-264. 被引量:105
  • 8陆海勇,赵伟,熊剑,赖际舟,刘建业.捷联惯导初始对准的超球体采样SRUKF算法[J].应用科学学报,2009,27(3):311-315. 被引量:3
  • 9杨萌,郝燕玲,高伟.基于SSUKF的粒子滤波算法研究[J].哈尔滨工程大学学报,2010,31(5):601-606. 被引量:3

引证文献2

二级引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部