系统工程与电子技术 ›› 2018, Vol. 40 ›› Issue (2): 267-272.doi: 10.3969/j.issn.1001-506X.2018.02.05

• 电子技术 • 上一篇    下一篇

多源信息融合的组合导航自适应联邦滤波算法

段睿1, 张小红1,2, 朱锋1   

  1. 1. 武汉大学测绘学院, 湖北 武汉 430079;
    2. 地球空间信息技术协同创新中心, 湖北 武汉 430079
  • 出版日期:2018-01-25 发布日期:2018-01-23

Adaptive federated filter for multi-sources information fusion in integrated navigation system

DUAN Rui1, ZHANG Xiaohong1,2, ZHU Feng1   

  1. 1. School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China;
    2. Collaborative Innovation Center of Geospatial Technology, Wuhan 430079, China
  • Online:2018-01-25 Published:2018-01-23

摘要: 全球卫星导航系统、捷联惯导、里程计、零速更新等多源信息的融合为地面移动测量系统提供了精确的位置和姿态参考信息。针对进行多源信息融合时,由于数学模型偏差和观测值粗差的影响,传统的联邦滤波不能有效隔离故障子系统的影响的问题,提出了利用验前新息计算联邦滤波的信息分配系数,基于联邦滤波和自适应滤波的等效性和抗差滤波原理,实现实时调整信息分配系数的自适应联邦滤波算法。通过一组车载数据的分析表明,自适应联邦滤波算法相对于传统联邦滤波算法,能有效地抵御观测值粗差和数学模型偏差的影响,显著提高了组合导航系统的精度和可靠性。

Abstract: The fusion of global navigation satellite system, strapdown inertial navigation system, odometer and zero velocity updates can provide accurate position and attitude references for ground mobile surveying systems. For the existences of mathematics model bias and measurement outliers, the traditional federated filter cannot isolate the interference from fault subsystems efficiently when fusing multisources information. Based on the equivalence of adaptive filter and federated filter and the principle of robust filter, an algorithm is proposed to calculate the information sharing coefficient by using the pre-innovation and then adjust it automatically. A field vehicle test shows that compared with the traditional federated filter the proposed adaptive federated filter can resist the measurement outliers and degrade the impact of the mathematics model errors effectively, and the accuracy and robustness of the integrated navigation system can be improved.

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