Journal of Navigation · 2013 · 45 citations · 21 references
ComputingAutonomous SystemsGeodesyGlobal Navigation Satellite SystemsSensor FusionAttitude DeterminationKalman FilteringNavigation SystemsAccuracyEarth-centered Earth-fixed FramesGlobal Positioning SystemInertial NavigationInertial Navigation SystemsState Vector EstimationUnscented Kalman FilterUnscented Kalman Filtering
A loosely coupled Inertial Navigation System (INS) and Global Positioning System (GPS) are studied, particularly considering the constant lever arm effect. A five-element vector, comprising a craft's horizontal velocities in the navigation frame and its position in the earth-centred and earth-fixed frame, is observed by GPS, and in the presence of lever arm effect, the nonlinear observation equation from the state vector to the observation vector is established and addressed by the correction stage of an unscented Kalman filter (UKF). The conditionally linear substructure in the nonlinear observation equation is exploited, and a computationally efficient refinement of the UKF called marginalized UKF (MUKF) is investigated to incorporate this substructure where fewer sigma points are needed, and the computational expense is cut down while the high accuracy and good applicability of the UKF are retained. A performance comparison between UKF and MUKF demonstrates that the MUKF can achieve, if not better, at least a comparable performance to the UKF, but at a lower computational expense.
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