摘要
非线性动态系统存在非线性和噪声不确定的问题,容积卡尔曼滤波对解算该类系统有较好的精度,为了提升导航系统对异常观测值的稳定性,对采样数据进行均值滤波处理,降低干扰较大的采样数据对于滤波结果的影响。用奇异值分解代替Cholesky分解,改善滤波稳定性,避免先验协方差非正定而降低滤波性能。最后通过引入抗差因子调节观测协方差矩阵,再次减少观测异常值对于滤波结果的影响。采用仿真实验进行分析,改进的抗差容积卡尔曼滤波算法对于减弱异常观测值影响有良好的效果。
The nonlinear dynamic system has problems of nonlinearity and noise uncertainty,and the cubature Kalman filter has better accuracy for solving such problems in the system.To improve the robustness of the navigation system against abnormal observations,the sampled data were average filtered to reduce the impact of the sampled data with greater interference on the filter.The singular value decomposition was used to replace the Cholesky decomposition to avoid the non-positive definite prior covariance reducing the filter stability.Finally,by introducing a robustness factor to adjust the observation covariance matrix,the effect of observation outliers on the filtering results was reduced again.Therefore,using simulation experiments for analysis,the improved robust cubature Kalman filter algorithm is effective for reducing the influence of abnormal observations.
作者
王姚宇
陈仁文
张祥
WANG Yao-yu;CHEN Ren-wen;ZHANG Xiang(State Key Laboratory of Mechanics and Control of Mechanical Structures,University of Aeronautics and Astronautics,Nanjing 210016,China;School of Information Science and Engineering,Southeast University,Nanjing 211102)
出处
《科学技术与工程》
北大核心
2021年第6期2356-2362,共7页
Science Technology and Engineering
基金
国家自然科学基金(51675265)
江苏高校优势学科建设工程资助项目(PAPD)。
