SINS静基座初始对准的超球体采样STFUKF算法

摘要

The initial alignment is a key technology for achieving high-precision inertial navigation. When used in initial alignment with large initial misalignment angles of SINS on stationary base, Unscented Kalman Filter ( UKF) has the shortages of large amount of calculation, low convergence speed and low estimation accuracy etc. To solve the problems, we combined the Spherical Simplex Transformation with the Strong Tracking Filtering UKF ( STFUKF) algorithm, which could improve the computing speed and alignment accuracy. We compared the performance of STFUKF with that of UKF and Kalman Filtering ( KF) by using digital simulation to a nonlinear SINS error model, and the result showed that the Spherical Simplex STFUKF algorithm has high precision, fine anti-interference performance and strong tracking capability.%初始对准是实现惯性导航高精度的一项关键技术.无迹滤波(UKF)在SINS系统静基座大方位失准角初始对准中计算量大,在不精确或错误的噪声统计情况下,收敛速度变慢,估计精度下降,甚至滤波发散.针对这一问题,将超球体采样与强跟踪无迹滤波(STFUKF)算法相结合,提高了运算速度和对准精度.利用SINS的非线性误差模型,通过数字仿真将卡尔曼滤波、UKF和STFUKF的性能进行比较,证明该方法具有精度高、抗干扰性好、跟踪能力强的特点.