不同的航向确定方法呈现不同的误差特性，通过多航向传感器的信息融合能够获得更稳定、准确的航向测量。本文提出了一种包含多个航向传感器数据融合和故障容错联邦卡尔曼滤波器的组合导航方法。该方法能够实现多个航向传感器的数据融合，同时还能实现传感器的在线故障检测和实时容错。首先基于输出误差协方差的权值法对航向测量进行最优融合，然后基于状态卡方和残差卡方设计了一个容错联邦卡尔曼滤波器，该滤波器能够检测并隔离故障的航向传感器。实测数据试验表明，该方法能够达到预期的舰艇组合导航系统的故障容错性能。
The different measurement methods of heading has different error characteristics, however, the more stable and accuracy heading measurement can be gained by muti-heading sensors data fusion. This paper present a scheme for integrated navigation system with applications of sensors data fusion and fault-tolerant Kalman filter(FTFK). It can complete data fusion 0f muti-heading sensors, detect faulty sensors online and conduct fault-tolerant in real time. First, implement optimal data fusion of muti-heading sensors by weighted method based on output error variance, then a faulty-tolerant Kalman filter scheme is designed, The FTKF can detect and isolate the faulty sensor by using fault detection based on method of state Chi-Square test and residual Chi-Square. The comparative analysis performance of experiment shows that the propose scheme may achieve the expected fault-tolerant performance in integrated navigation system.
2019,41(4): 114-118 收稿日期：2017-09-05
DOI：10.3404/j.issn.1672-7649.2019.04.022
分类号：U666
基金项目：国家自然科学基金资助项目（41506220）
作者简介：戴海发(1990-),男,博士研究生,主要从事组合导航技术研究
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