MEKF With Navigation Frame Attitude Error Parameterization for INS/GPS

The multiplicative extended Kalman filter (MEKF) is an attractive method for inertial navigation system and Global Positioning System (INS/GPS) integration due to its flexibility and computational efficiency. Traditionally, in MEKF, the attitude error that is used as the local filtering state is always expressed in the body frame. With such definition, the resulting attitude error model contains inevitable disturbance, which may degrade the filtering performance. Motived by the aforementioned fact, this work revisits the MEKF for INS/GPS with the utilization of navigation frame attitude error model in the filter. The presentation of MEKF in this paper is in a self-contained manner, which is tutorial in nature and clearly defines all involved attitude and attitude errors for frame transformation. Since there is no noise/disturbance contaminated factor in the model, the proposed model possesses advantages in terms of both robustness and accuracy. The subtle differences that arise between the used navigation frame attitude error model and traditional body frame attitude error model in MEKF are discussed and evaluated based on simulation and field test results.