Applying CDKF (central difference Kalman filter) to initial alignment of SINS for large misalignment angles

Section 1 of the full paper briefs the nonlinear error model of large misalignment angles of SINS (strapdown inertial navigation system). Section 2 explains how we apply the CDKF to the initial alignment of SINS for large misalignment angles; its core is presented in subsection 2.2, whose title is the CDKF algorithm; subsection 2.2 obtains the CDKF algorithm by applying the central difference transform to the state estimation of the nonlinear error model and presents the six-step procedure, which is detailed by eqs. (19) through (35). The simulation results, given in Figs. 1, 2 and 3 and Table 1, and their analysis show preliminarily that: (1) with our CDKF algorithm, the level alignment precision can be within 0.18' and the heading alignment precision can be within 1.63' under large misalignment angles; (2) compared with EKF, our CDKF algorithm does not need to calculate the Jacobian matrices and thus has better reliability and precision; (3) compared with UKF, our CDKF algorithm has higher precision and is easier to implement because it uses only one adjustable parameter instead of three in the UKF circumstances.