Research on the Relationship between Information Fusion Method and Information Failure Mode in Integrated Navigation System

B. Han, B. Hu
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Abstract

Abstract:On the basis of the basic principles of weighted fusion, Kalman filtering and BP neural networks, the basic principles of information fusion methods used in integrated navigation systems are expounded. Through the analysis of the basic principles, the association of information fusion methods commonly used in integrated navigation systems and information failure modes is obtained: the information fault mode of weighted fusion method The model is closely related to the specific weight allocation method, which depends on the fault mode of the sensor or sub-system in which the weight is dominant; the information fault mode of the Kalman filtering information fusion method is a continuous mutation fault corresponding to the nonlinear time interval of the system; the information fault mode of the BP neural network method is gradual with time. The information failure mode of the BP neural network method is a slowly varying fault that gradually accumulates over time. Starting from the complexity associated with the information fusion method and the information failure mode, it is pointed out that in order to systematically express the relationship between the information fusion method and the information failure mode, further research can be carried out.
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组合导航系统信息融合方法与信息失效模式的关系研究
文摘:在加权融合、卡尔曼滤波和BP神经网络的基本原理的基础上,阐述了组合导航系统中信息融合方法的基本原理。通过对基本原理的分析,得出了组合导航系统中常用的信息融合方法与信息故障模式的关联:加权融合方法的信息故障模式该模型与具体的权重分配方法密切相关,该方法取决于权重占主导地位的传感器或子系统的故障模式;卡尔曼滤波信息融合方法的信息故障模式是与系统的非线性时间间隔相对应的连续突变故障;BP神经网络方法的信息故障模式随着时间的推移是渐进的。BP神经网络方法的信息失效模式是一种随着时间的推移逐渐积累的缓慢变化的故障。从信息融合方法和信息失效模式的复杂性出发,指出为了系统地表达信息融合方法与信息失效模式之间的关系,可以进行进一步的研究。
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