With the development of high-accuracy inertial navigation system inertial sensors, such as ring laser gyroscopes and atomic spin gyroscopes, it is increasingly important to improve the strapdown inertial navigation algorithms to match such high-accuracy inertial sensors. For example, the existing inertial navigation algorithms have not taken into account the triple-cross-product term of noncommutativity error. However, theoretical analysis demonstrates that the ignored triple-cross-product term is nonignorable under coning motion with constant angular rate precession environments. In this paper, a new high-accuracy rotation vector algorithm is proposed for strapdown inertial navigation. The Taylor series about time is used for error analysis and optimization of the new algorithm. General maneuvers and coning motion with constant angular rate precession environments are considered in establishing the coefficient equations in the proposed algorithm. Error drift equations are given after the error compensation. Normalized quaternion under coning motion with constant angular rate precession environments and Savage's severe integrated angular-rate profiles are used to numerically verify the new algorithm. The results
Manuscriptindicate that the new high-order attitude updating algorithm can improve inertial navigation accuracy.NOMENCLATURE δφ c (t) = coning integral over the time interval from t m−1 to t δφ hA (t) = the integral of the triple-cross product noncommutativity rate vector over the time interval from t m−1 to t related to the coning motion, which is called the triple-cross-product term part A δφ hB (t) = the integral of the triple-cross-product noncommutativity rate vector over the time interval from t m−1 to t related to the high dynamic motion, which is called the triple-cross-product term part B δφ hA (t) = algorithms for the triple-cross-product term part A δφ hB (t) = algorithms for the triple-cross-product term part B δφ hA = nonperiodic vector of the triple-cross-product term part A in one updating cycle δφ hB = nonperiodic vector of the triple-cross-product term part B in one updating cycle δφ hA = nonperiodic vector of the triple-cross-product term part A algorithms δφ hB = nonperiodic vector of the triple-cross-product term part B algorithms α N+1−i (t) = gyro data samples spaced backward in time from time t α N+1−j (t) α N+1−k (t) ς ij = coefficients of uncompressed frequency series coning algorithms and triple-cross-product term part A's algorithms η (N+i−1) = coefficients of triple-cross-product term part B's algorithms (N+j −1) (N+k−1) a, b = coning motion amplitude c = coefficient of constant angular-rate precession = coning frequency T 0 = sampling period T = attitude updating cycle N = total number of samples used in one attitude updating cycle 1178 IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS VOL. 51, NO. 2 APRIL 2015 n = number of samples in the current iteration time interval m = computer interval index, where the subscript indicates parameter value at computer cycle m o () = a...