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Integrated Navigation Based on Robust Estimation Outputs of Multi-sensor Measurements and Adaptive Weights of Dynamic Model Information

Integrated Navigation Based on Robust Estimation Outputs of Multi-sensor Measurements and Adaptive Weights of Dynamic Model Information
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摘要 An integrated navigation based on the kinematic or dynamic state model and the raw measurements has the advantages of high redundancy, high reliability, as well as high ability of fault tolerance and simplicity in calculation. In order to control the influences of measurements outliers and the kinematic model errors on the integrated navigation results, a robust estimation method and an adaptive data fusion method are applied. An integrated navigation example using simulated data is performed and analyzed. An integrated navlgation based on the kinematic or dynamic state model and the raw measurements has the advantages of high redundancy, high reliability, as well as high ability of fault tolerance and simplicity in calculation. In order to control the influences of measurements outliers and the kinematic model errors on the integrated navigation results, a robust estimation method and an adaptive data fusion method are applied. An integrated navigation example using simulated data is performed and analyzed.
出处 《Geo-Spatial Information Science》 2005年第3期201-204,224,共5页 地球空间信息科学学报(英文)
基金 Project supported by the National Outstanding Youth Science Foundation ( No.49825107) and the Natural Science Foundation ( No.40244002 No.40174009) .
关键词 综合导航系统 全球定位系统 传感器 卫星导航 卫星定位 integrated navigation multi-sensor robust estimation adaptive data fusion
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参考文献2

  • 1Y. Yang,H. He,G. Xu.Adaptively robust filtering for kinematic geodetic positioning[J].Journal of Geodesy (-).2001(2-3)
  • 2K. R. Koch,Y. Yang.Robust Kalman filter for rank deficient observation models[J].Journal of Geodesy (-).1998(7-8)

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