期刊
SENSORS
卷 12, 期 7, 页码 8877-8894出版社
MDPI AG
DOI: 10.3390/s120708877
关键词
matrix Kalman filter; Lie derivatives; observability of nonlinear systems; navigation; vision; inertial measurement unit
资金
- Research Fund for the Doctoral Program of Higher Education of China [20069998009]
- New Century Excellent Talents in University of China [NCET-07-0225]
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.
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