Nonlinear Transfer Alignment Model and Filtering Algorithm for Strapdown Inertial Navigation System of Shipborne Weapons
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摘要: 为了满足舰载武器初始对准高精度和快速性的要求, 更好地解决舰载武器在大失准角情况下的传递对准问题, 提出了一种结合基于四元数的非线性传递对准模型与非线性无迹卡尔曼滤波(UKF)算法的方法, 推导并建立了舰载武器捷联惯导系统(SINS)的非线性误差模型。该模型采用姿态四元数表示姿态误差, 以提高姿态解算时的快速性和精度, 选用速度加姿态作为量测量, 以提高系统的可观测性, 采用奇异值分解(SVD)方法解决了方差阵的病态问题, 以确保算法的鲁棒性, 仿真结果表明, 该方法不仅解决了舰载武器在大失准角情况下的传递对准问题, 而且能够有效提高传递对准的精度和快速性, 其计算精度和对准时间满足系统设计要求。Abstract: To satisfy the requirement of fast reaction and high precision of initial alignment for shipborne weapons, and to enhance the transfer alignment for shipborne weapons with large misalignment, we present a method of combining the rapid transfer alignment model based on quaternion and the nonlinear unscented Kalman filter (UKF) algorithm, and establish a nonlinear error model for strapdown inertial navigation system(SINS) of shipborne weapons. This error model introduces quaternion to describe the attitude errors in order to enhance the speed and accuracy in calculating attitude. We select a velocity and attitude matching approach to improve the observability of the system, and solve the ill-condition of covariance matrix of the traditional nonlinear UKF filter by using singular value decomposition(SVD) to ensure the algorithm robustness. The simulation results show that the proposed method can effectively improve the precision and speed of transfer alignment for shipborne weapons with large misalignment, and its calculation accuracy and alignment time meet the design requirements of the system.
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