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System Modeling and Non-Linear Estimation Performance Comparison of Monocular Vision based Integrated Navigation System |
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PP: 413-420 |
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doi:10.18576/amis/100205
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Author(s) |
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Dae Hee Won,
Sukchang Yun,
Young Jae Lee,
Sangkyung Sung,
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Abstract |
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| This paper presents and compares the performance of nonlinear estimation filters for the inertial SLAM (Simultaneous
Localization and Mapping) integrated navigation system including the extended Kalman filter, the unscented Kalman filter and
the particle filter. A computer simulation is conducted to analyze the navigation accuracy as well as the capability of real-time
implementation by individual filter using a monocular vision based navigation model. The detail model for the linear filter design
and the initial delayed localization of the target features were investigated. Simulation results show that the unscented Kalman filter has
better performance in perspective of both the navigation performance and the feasibility of real-time implementation. |
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