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作 者:李寿鹏 穆荣军[1] 崔乃刚[1] 龙腾 LI Shoupeng;MU Rongjun;CUI Naigang;LONG Teng(School of Astronautics,Harbin Institute of Technology,Harbin 150001,China)
出 处:《中国惯性技术学报》2020年第3期293-301,共9页Journal of Chinese Inertial Technology
基 金:国家高技术研究发展计划(863计划)(2015AA7026083)。
摘 要:在大安装偏差快速传递对准中,模型线性化误差会导致卡尔曼滤波器(KF)估计有偏。针对该问题,提出了一种基于闭环卡尔曼滤波器(CLKF)的传递对准方法。基于安装关系估计值与主惯导姿态建立子惯导粗基准,使子惯导载体系失准角为小角度,从而降低了线性化误差对KF估计精度的影响。进一步采用状态反馈机制修正子惯导状态与安装关系估计值,使子惯导基准载体系和计算载体系逐渐逼近标称载体系,以保证系统在整个传递对准过程中始终处于良好的线性状态。仿真结果表明,CLKF估计精度不随系统非线性增强而下降,与无迹卡尔曼滤波器(UKF)相当且优于KF;CLKF计算量仅为UKF的3%,与KF相当,显著提高了线性滤波器的估计精度,同时有效避免了采用非线性滤波器而引起计算量较大的问题。In rapid transfer alignment with large physical misalignment angles,Kalman filter(KF)obtains biased estimation due to the model linearization error.To solve this problem,a transfer alignment approach based on closed-loop Kalman filter(CLKF)is presented.A coarse reference of the slave inertial navigation system(INS)is established by combining the estimated physical misalignment angles with the attitude of the master INS,which minimizes the misalignment angles of the slave INS and reduces the influence on the estimation accuracy of KF induced by the linearization error.Meanwhile,the slave INS state and the estimation of the misalignment angles are corrected with state feedback,which drives the slave INS reference body frame and the calculated body frame converging to the nominal body frame gradually.So that the whole system is always kept in a good linear state in the entire transfer alignment process.The simulation results show that the estimation accuracy of CLKF is equal to UKF and better than KF,which is not affected by the increase of system nonlinearities.Analogous to KF,the computational cost of CLKF is only 3%of UKF,which improves the estimation accuracy of the linear filter significantly and effectively avoids the problem of large computational burden caused by applying the nonlinear filter.
关 键 词:非线性传递对准 闭环卡尔曼滤波 快速传递对准 状态反馈 大安装偏差
分 类 号:V249.322[航空宇航科学与技术—飞行器设计]
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