Unscented粒子滤波在静基座捷联惯导系统大方位失准角初始对准中的应用研究

 静基座大方位失准角的捷联惯导系统误差方程是非线性的，Unscented粒子滤波从非线性系统状态向量概率分布出发，结合Unscented卡尔曼滤波和粒子滤波的特点，无需对非线性系统模型进行处理而能达到较高的滤波精度。本文对Unscented粒子滤波进行了研究，并结合重采样算法，运用于捷联惯导系统静基座大方位失准角初始对准中，计算结果验证了该方法的有效性与优越性。

Study on Unscented Particle Filter Applied in Initial Alignment of Large Azimuth Misalignment on Static Base of SINS

The error function is nonlinear when the azimuth angle of strapdown inertial navigation system (SINS) on stable base is large,and a new filter that results from using a Unscented Kalman filter and particle filter for state vector probability density distribution generation called Unscented particle is researched in this paper.This filter is applied in initial alignment of SINS with large azimuth angle on stable base,and the simulation results show that the new filter is more effective and its precision is higher than that of the Unscented Kalman filter.