Analysis of the NED and ECEF Covariance Propagation for the Navigational Extended Kalman Filter
- Paper number
IAC-07-B2.I.14
- Author
Mr. Frank Centinello III, State University of New York at Buffalo, United States
- Coauthor
Mr. John L. Crassidis, United States
- Year
2007
- Abstract
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 an optimal 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 a first-order 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 both parameterizations of the EKF result in nearly the same accuracy, but that the ECEF filter converges slightly faster.
- Abstract document
- Manuscript document
IAC-07-B2.I.14.pdf (🔒 authorized access only).
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