Analysis of the NED and ECEF covariance propagation for the navigational extended Kalman filter
Centinello, Frank J., III
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The Extended Kalman Filter (EKF) is the most widely used algorithm for the estimation of IMU bias and scale factor errors for GPS/INS navigation. The EKF is a suboptimal sequential state estimator for use with nonlinear systems. The navigational EKF can be programmed in geocentric (ECEF) and navigational (latitude, longitude, and altitude) coordinates. This is a presentation of the affect the choice of coordinate frame has on the covariance propagation of the EKF. For the EKF, a model's error dynamics are approximated using the first-order term of Taylor series representation of the equations of motion. For this study, the choice of reference frame greatly affects the complexity of this approximation. Key filter differences are presented, and the results several filter performance tests are shown. It was found that the ECEF parameterization of the EKF allows for more accurate estimation of attitude, position, and velocity, and that both parameterizations estimate inertial measurement unit errors to the same accuracy.