SINS基于非线性量测的大失准角初始对准算法

针对陆用捷联惯导系统(SINS)大失准角初始对准问题，提出一种基于二阶非线性量测的二阶泰勒级数展开的初始对准算法。首先，将大失准角非线性对准问题，转化为具有线性系统方程和二阶非线性量测方程的滤波问题。然后，设计基于二阶非线性量测方程的二阶泰勒级数展开的滤波算法，可以在任意姿态和无初值条件下进行初始对准和参数估计。最后进行车载对准试验，结果表明，新算法可以在300s内完成实现大失准角初始对准，对准精度与传统分段对准算法相当。

Nonlinear Measurement Based SINS Initial Alignment Algorithm Under Large Misalignment Angle

Aiming at the problem of strapdown inertial navigation (SINS) initial alignment with large misalignment angles for land vehicles, an initial alignment algorithm is proposed based on the second order Taylor series expansion of second order nonlinear measurements. Firstly, the nonlinear alignment is transformed into a filtering problem with linear system equation and second order nonlinear measurement equation. Then, a filtering scheme is designed based on the exact Taylor series expansion of the measurement equation. Under arbitrary attitude and without initial value, the initial alignment and parameter estimation can be attained by using the linear Kalman Filtering scheme. Finally, the alignment experiments are performed on a land vehicle, and the results indicate that the new algorithm has an equal alignment precision with respect to the traditional two-phase alignment method within 300 seconds.