ACDKF在SINS大方位失准角初始对准中的应用  

Application of ACDKF in initial alignment of large azimuth misalignment in SINS

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,黑龙江哈尔滨150001

出　　处：《华中科技大学学报（自然科学版）》2012年第12期80-84,共5页Journal of Huazhong University of Science and Technology(Natural Science Edition)

基　　金：国家自然科学基金资助项目(60674087)

摘　　要：将可以估计系统参数、噪声统计特性和修正滤波增益的自适应估计方法引入到CDKF算法中,并将其应用到SINS大方位失准角初始对准中,实现SINS大方位失准角初始对准,解决了噪声特性不准确的非线性问题,避免了线性化误差对滤波精度的影响,克服了噪声统计特性不准确的局限性,进一步提高了导航精度.采用自适应中心差分卡尔曼滤波(ACDKF)进行初始对准,提高了CDKF算法的收敛性和系统的稳定性.仿真结果表明:ACDKF能够克服噪声统计模型不准确对滤波结果的影响,对失准角的估计精度优于CDKF,进一步提高了系统的精度和可靠性.Method of adaptive estimation was introduced into CDKF（central difference Kalman filter）,which not only can estimate system parameter and noise statistics,but also can modify filter gain.As a result,This method was utilized in SINS（strapdown inertial navigation system）initial alignment with large azimuth misalignment to achieve SINS initial alignment with large azimuth misalignment,solve the nonlinear problem with inaccurate noise characteristics,avoid the affection of linearization error on filter accuracy,overcomes the limitation of inaccurate noise characteristics,and further improve navigation accuracy.ACDKF（adaptive central difference Kalman filter）was utilized in initial alignment,which improved the convergence of CDKF and system stability.The simulation results demonstrate that ACDKF can overcome the affection of inaccurate noise statistics on filter results,and the estimation on misalignment angle is more accurate than CDKF,which further improves the system accuracy and reliability.

关 键 词：自适应算法 大方位失准角 捷联惯导系统 初始对准 自适应中心差分卡尔曼滤波(ACDKF) 

分 类 号：TN967.2[电子电信—信号与信息处理]