Federated IMM-UKF Algorithm for Multi-sensor Data Fusion

被引:2
|
作者
Xu, Tianlai [1 ]
机构
[1] Harbin Inst Technol, Inst Spacecraft Dynam & Control, Harbin 150006, Heilongjiang, Peoples R China
来源
MATERIALS PROCESSING AND MANUFACTURING III, PTS 1-4 | 2013年 / 753-755卷
关键词
data fusion; federated filter; Interacting Multiple Model; UKF;
D O I
10.4028/www.scientific.net/AMR.753-755.2117
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The accuracy of multi-sensor navigational data fusion by federated Kalman filter will be reduced in condition that the system's dynamics model is nonlinear and the noise statistical properties are unknown. To address this problem, a federated Interacting Multiple Model-Unscented Kalman Filteing (IMM-UKF) algorithm is presented. The UKF is a nonlinear estimation method which can achieve the accuracy at least to the second-order. The IMM estimation algorithm is one of the cost-effective adaptive estimation algorithm for systems involving parametric changes. The combination of IMM with UKF could deal with the problem of nonlinear filtering with uncertain noise. Simulation results show that the method can improve the accuracy of INS/GPS/odometer integrated navigation.
引用
收藏
页码:2117 / 2120
页数:4
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