捷联惯导初始对准的超球体采样SRUKF算法

应用科学学报 ›› 2009, Vol. 27 ›› Issue (3): 311-0315.

捷联惯导初始对准的超球体采样SRUKF算法

陆海勇，赵伟，熊剑，赖际舟，刘建业

南京航空航天大学导航研究中心，南京210016

收稿日期:2008-08-26 修回日期:2009-02-06 出版日期:2009-05-28 发布日期:2009-05-28
通信作者: 刘建业，教授，博导，研究方向：惯性组合导航、卫星定位系统、智能交通定位、测控系统，E-mail:ljyac@nucc.edu.cn

SINS Initial Alignment Based Spherical Simplex Transformation SRUKF Algorithm

Navigation Research Center, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

Received:2008-08-26 Revised:2009-02-06 Online:2009-05-28 Published:2009-05-28

摘要/Abstract

摘要：

平淡卡尔曼滤波(UKF)在捷联惯导系统静基座大方位失准角初始对准中计算量大，且滤波数值不稳定. 针对这一问题，该文将超球体采样策略与平方根UKF(SRUKF)算法相结合，提出一种改进的SRUKF算法. 该算法在保证其滤波精度和UKF算法相当的前提下，通过引入超球体采样减少了采样点数，提高了计算速度. 并以协方差阵的平方根矩阵代替协方差阵参加递推运算，减少了计算机舍入误差，提高了滤波数值稳定性. 仿真结果表明，该算法在保证初始对准滤波精度的前提下降低了计算量，提高了滤波性能.

关键词: 超球体采样 , 平方根滤波 , 初始对准

Abstract:

To reduce the amount of calculation and solve the instability problem in the strapdown inertial navigation system(SINS) initial alignment of large azimuth misalignment, this paper proposes a modified square root unscented Kalman filter (SRUKF). The filter uses the spherical simplex unscented transformation to reduce the number of sigma points to speed calculation without sacrificing the filter precision. To reduce rounding errors and improve stability, the covariance matrix is replaced with a new matrix whose entries are square roots of the covariance matrix. Simulation results show that the spherical simplex SRUKF algorithm can significantly reduce the computation load and provide better filtering performance with accurate alignment.

Key words: spherical simplex transformation , square-root filter , initial alignment

中图分类号:

V249.32

陆海勇，赵伟，熊剑，赖际舟，刘建业. 捷联惯导初始对准的超球体采样SRUKF算法[J]. 应用科学学报, 2009, 27(3): 311-0315.

LU Hai-yong, ZHAO Wei, XIONG Jian, LAI Ji-zhou, LIU Jian-ye. SINS Initial Alignment Based Spherical Simplex Transformation SRUKF Algorithm[J]. Journal of Applied Sciences, 2009, 27(3): 311-0315.