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针对舰船捷联惯性导航系统姿态控制计算精度要求,提出一种高阶矩匹配UKF(high-order moment matching UKF,Ho MM-UKF)的SINS系统四元数模型姿态估计算法.在UKF迭代递推计算过程中利用高阶矩匹配方法计算系统状态参数的预测采样点集及其权值的概率分布平均偏态和峰值,使其精确逼近状态参数最优估计.采用四元数姿态建模方法构建新型SINS状态变量与噪声向量相关的姿态方程模型,利用伪观测向量构建观测噪声与四元数相关的观测方程模型,设计系统噪声方差分离计算算法开展系统噪声方差计算,引入拉格朗日乘子算法计算四元数估计均值,最后利用SINS四元数姿态估计模型对HoMM-UKF算法开展仿真试验研究.通过UKF算法、CDKF算法与HoMM-UKF算法对比,验证了HoMM-UKF算法计算精度高,并且算法计算量负担较小,计算效率较高.
In order to meet the requirements of accuracy of attitude control of ship strapdown inertial navigation system (SINS), this paper proposes a pose estimation algorithm for quaternionic SINS system with high order moments matching UKF (Ho MM-UKF) In the process of push calculation, the average skewness and peak value of the probability distribution of the predicted sampling point sets and their weights of the system state parameters are calculated by using the high-order moment matching method to make it approximate the optimal estimation of the state parameters accurately. The quaternion attitude modeling method The attitude equation model related to the noise vector of SINS state variables is constructed. The observatory equation related to the observed noises and quaternions is constructed by using pseudo observation vector. The system noise variance calculation algorithm is designed to calculate the system noise variance. Lagrange multiplication Finally, the HoMM-UKF algorithm is simulated by SINS quaternion attitude estimation model.Compared with the HoMM-UKF algorithm by the UKF algorithm and the HoMM-UKF algorithm, the computational accuracy of the HoMM-UKF algorithm is verified , And the computational burden of the algorithm is smaller and the calculation efficiency is higher.