基于修正的自适应平方根容积卡尔曼滤波算法  

Adaptive square-root cubature Kalman filter algorithm based on amending

作　　者：李春辉 马健[1] 杨永建 肖冰松[1] 邓有为[1] 盛涛 LI Chunhui;MA Jian;YANG Yongjian;XIAO Bingsong;DENG Youwei;SHENG Tao(Aeronautics Engineering College, Air Force Engineering University, Xi’an 710038, China;School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, China)

机构地区：[1]空军工程大学航空工程学院,陕西西安710038 [2]西北工业大学电子信息学院,陕西西安710072

出　　处：《系统工程与电子技术》2021年第7期1824-1830,共7页Systems Engineering and Electronics

基　　金：空军工程大学校长基金(XZJ2020039)资助课题。

摘　　要：目标建模不确定性会造成滤波算法性能下降,通过构建强跟踪滤波器(strong tracking filter,STF)可以提升滤波算法的自适应性,但是构建STF时存在理论推导复杂、求解计算量大等局限和不足,针对上述问题,在平方根容积卡尔曼滤波(square-root cubature Kalman filter,SRCKF)的基础上,提出一种基于修正的自适应SRCKF算法。该算法通过设置判定门限和修正准则,直接对状态预测值或滤波增益进行修正以平衡先验的预测值和后验反馈的量测值在滤波中所占的比重,进而减小状态估计误差。仿真结果表明,所提算法具有在目标状态突变和量测非线性时的良好滤波性能和数值稳定性,同时相比较需要计算渐消因子的STF算法,该算法在计算量和收敛速度上具有优势。The uncertainty of target modeling will lead to the performance degradation of the filter algorithm,and the self-adaptability of the filter algorithm can be improved by constructing strong tracking filter(STF).However,there are limitations and deficiencies in the construction of STF,such as complex theoretical derivation and large amount of calculation.To solve the above problems,an adaptive square-root cubature Kalman filter(SRCKF)algorithm based on amending is proposed which is based on SRCKF.By setting judgment threshold and amending rules,the proposed algorithm directly amends the predicted state value or filter gain to balance the proportion of the predicted prior value and the measured posterior feedback value in the filtering,which can reduce the state estimation error.Simulation results show that the algorithm has good filtering performance and numerical stability when the target state is suddenly changed and the measurement is nonlinear.Meanwhile,compared with the STF algorithm which needs to calculate the fading factor,the proposed algorithm has advantages in calculation amount and convergence speed.

关 键 词：目标建模 平方根容积卡尔曼滤波 修正算法 自适应滤波 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]