期刊文献+

某型机载惯性/卫星/大气多信息融合MEMS航姿系统的设计与实现

Design and Implementation of an Airborne Inertial/Satellite/Air Data Integrated MEMS AHRS
原文传递
导出
摘要 针对机载MEMS航姿系统中器件精度低且易受干扰导致其姿态性能降低的问题,提出了一种基于大气/卫星信息辅助的航姿系统融合方案。构建了多源传感信息辅助下的综合航姿系统方案,所设计系统具有多种工作运行模式,可根据传感器可用状态实现滤波器的无缝切换,建立了组合导航系统状态和量测模型,采用Kalman滤波方法实现多源信息的融合与估计,并开展了原理样机的跑车试验。试验结果表明,所设计的融合方案能有效保障航姿系统的可靠性与精度,具有较高的工程应用价值。 Aiming at the problem of reduced attitude performance of airborne MEMS AHRS which is caused by the low device accuracy and its susceptible to interference,a fusion scheme based on air data/satellite information is proposed in the paper. Integrated posture system aided by multi-source sensor information is established. The designed system has a variety of operation mode,which can achieve a seamless filter switch according to the available states of sensors. The state and measurement model of the integrated navigation system are built. The fusion and estimation of multi-source information is realized by Kalman filter method,and the proposed scheme is verified through practical tests. Test results show that the proposed fusion scheme can effectively guarantee the reliability and precision of AHRS,which has good engineering application value.
作者 曹阳 赖际舟 柳敏 叶素芬 CAO Yang;LAI Ji-zhou;LIU Min;YE Su-fen(College of Automation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106)
出处 《导航与控制》 2018年第2期53-58,106,共7页 Navigation and Control
基金 六大人才高峰(编号:2015-XXRJ-005)
关键词 微机电系统 航姿系统 卫星导航系统 KALMAN滤波 micro electro mechanical system (MEMS) attitude heading reference system (AHRS) satellite navigation system Kalman filter
  • 相关文献

参考文献5

二级参考文献44

  • 1高钟毓,牛小骥,郭美凤.Quaternion-Based Kalman Filter for Micro-machined Strapdown Attitude Heading Reference System[J].Chinese Journal of Aeronautics,2002,15(3):171-175. 被引量:18
  • 2黄旭,王常虹.磁强计和微机械陀螺/加速度计组合定姿的扩展卡尔曼滤波器设计[J].黑龙江大学自然科学学报,2005,22(4):454-458. 被引量:13
  • 3施闻明,徐彬,陈利敏.捷联式航姿系统中四元素算法Kalman滤波器的实现研究[J].自动化技术与应用,2005,24(11):6-8. 被引量:15
  • 4BARBOUR N M. Inertial navigation sensors[R]. Charles Stark Draper Lab Inc Cambridge Ma, 2010.
  • 5ROHAC J,REINSTEIN M,DRAXLER K. Data pro- cessing of inertial sensors in strong-vibration enviro- nment[C]//2011 IEEE 6th International Conference on Intelligent Data Acquisition and Advanced Com- puting System: Technology and Applications, 2011: 71-75.
  • 6LAI Y C, JAN S S. Attitude estimation based on fusion of gyroscopes and single antenna GPS for small UAVs under the influence of vibration [J ]. GPS Solution, 2010, 15(1): 67-77.
  • 7LOPES H D, KAMPEN E, CHU Q P. Attitude determination of highly dynamic fixed-wing uavs with gps/mems-ahrs integration [ C]//AIAA Guidance, Navigation, and Control Conference. 2012: 4460.
  • 8Ming Liu,Haijun Wang.Application of the Adaptive Two-stage EKF Algorithm inGeomagnetic Aided Inertial Navigation. The2ndInternational Conference onIntelligent Control and Information Processing . 2011
  • 9De Marina, Hector Garcia,Pereda, Fernando J.,Giron-Sierra, Jose M.,Espinosa, Felipe.UAV attitude estimation using unscented Kalman filter and TRIAD. IEEE Transactions on Industrial Electronics . 2012
  • 10B. Grandvallet,A. Zemouche,M. Boutayeb.Real-Time Attitude-IndependentThree-Axis Magnetometer Calibration for Spinning Projectiles:A Sliding WindowApproach. IEEE Transactions on Control Systems Technology . 2013

共引文献52

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