Observability Analysis of a Matrix Kalman Filter-Based Navigation System Using Visual/Inertial/Magnetic Sensors

被引:17
作者
Feng, Guohu [1 ]
Wu, Wenqi [1 ]
Wang, Jinling [2 ]
机构
[1] Natl Univ Def Technol, Coll Mechantron & Automat, Changsha 410073, Hunan, Peoples R China
[2] Univ New S Wales, Sch Surveying & Spatial Informat Syst, Sydney, NSW 2052, Australia
基金
高等学校博士学科点专项科研基金;
关键词
matrix Kalman filter; Lie derivatives; observability of nonlinear systems; navigation; vision; inertial measurement unit; ORIENTATION;
D O I
10.3390/s120708877
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
A matrix Kalman filter (MKF) has been implemented for an integrated navigation system using visual/inertial/magnetic sensors. The MKF rearranges the original nonlinear process model in a pseudo-linear process model. We employ the observability rank criterion based on Lie derivatives to verify the conditions under which the nonlinear system is observable. It has been proved that such observability conditions are: (a) at least one degree of rotational freedom is excited, and (b) at least two linearly independent horizontal lines and one vertical line are observed. Experimental results have validated the correctness of these observability conditions.
引用
收藏
页码:8877 / 8894
页数:18
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