Application of simplified UKF in SINS initial alignment for large misalignment angles

SINS nonlinear error model was deduced based on the concept of Euler platform error angles(EPEA) with large initial misalignment angles, and this nonlinear error model could no longer be presented by using the classical additive noise models. To reduce the calculation burden, a simplified UKF(unscented Kalman filter) filtering algorithm was derived under the situation that both process noise and measurement noise were complex additive noise with linear measurement equation. The simplified UKF algorithm is identical to that of classical Kalman filter except for the predicting of states and their covariance matrix by unscented transformation (UT) in nonlinear state model. In the end, SINS initial alignment simulation tests under large EPEA were executed, and the results verified the proposed SINS error model and the simplified UKF algorithm.