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

Sensors

Guohu Feng¹  Wenqi Wu¹ 

[1] The College of Mechatronics and Automation, National University of Defense Technology, Changsha 410073, Hunan, China; E-Mail:

关键词: matrix Kalman filter;    Lie derivatives;    observability of nonlinear systems;    navigation;    vision;    inertial measurement unit;   

DOI  :  10.3390/s120708877

来源: mdpi

【 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.

【 授权许可】

CC BY   
© 2012 by the authors; licensee MDPI, Basel, Switzerland.