自适应平方根中心差分卡尔曼滤波算法在捷联惯性导航系统大方位失准角初始对准中的应用  

Application of adaptive SRCDKF in SINS initial alignment with large azimuth misalignment

作　　者：郝燕玲[1] 牟宏伟 

机构地区：[1]哈尔滨工程大学自动化学院,哈尔滨150001

出　　处：《吉林大学学报（工学版）》2013年第1期261-266,共6页Journal of Jilin University:Engineering and Technology Edition

基　　金：国家自然科学基金项目(60674087)

摘　　要：提出了一种自适应平方根中心差分卡尔曼滤波(ASRCDKF)算法,并应用于捷联惯性导航系统(SINS)大方位失准角初始对准中。ASRCDKF算法以中心差分变换为基础,基于平方根滤波能够克服发散的思想,利用协方差平方根代替协方差参加递推运算,并将自适应估计原理引入该算法中,不仅克服了扩展卡尔曼滤波产生线性化误差和计算雅可比矩阵的不足,而且减小了计算量,保证了数值稳定性。同时,ASRCDKF算法解决了传统滤波算法过度依赖系统动态模型和噪声统计特性先验知识的问题。最后通过滤波仿真证明了ASRCDKF算法在SINS大方位失准角初始对准中的有效性和优越性。An Adaptive Square Root Central Difference Kalman Filter （ASRCDKF） algorithm is proposed, which is used in the initial alignment of Strapdown Inertial Navigation System （SINS） with large azimuth misalignment angle. The basis of this algorithm is central difference transform, and square root of covariance is used instead of covariance in reeursive calculation based on the theory that square root filter can overcome filter divergence. In addition, adaptive estimation principle is introduced in this algorithm. The ASRCDKF algorithm not only overcomes the shortcomings that extended Kalman filter can generate linear error and it needs to calculate Jacobian matrix, but also reduces calculation amount to ensure numerical stability. Furthermore, this algorithm solves the problem that traditional filter algorithm relies on a prior knowledge of the system dynamic model and noise statistic characteristics. Simulation results fully verify the effectiveness and superiority of the ASRCDKF algorithm in SINS initial alignment with large azimuth misalignment angle.

关 键 词：信息处理技术 大方位失准角 捷联惯导系统 初始对准 

分 类 号：TN967.2[电子电信—信号与信息处理]