CAJ | 학술논문

针对强跟踪滤波器（STF）的理论局限性及不良测量导致的滤波性能下降问题，提出了一种强跟踪自适应平方根容积卡尔曼滤波（SRCKF）算法。利用新息协方差匹配原理，建立对不良测量具有鲁棒性的自适应SRCKF 。基于STF的理论框架，采用自适应SRCKF代替扩展卡尔曼滤波构建强跟踪自适应SRCKF 。该算法兼具STF与自适应SR-CKF的优点，在系统同时存在模型不确定性及不良测量时具有良好的滤波性能。仿真验证了所建算法的有效性。
침대강근종려파기（STF）적이론국한성급불량측량도치적려파성능하강문제，제출료일충강근종자괄응평방근용적잡이만려파（SRCKF）산법。이용신식협방차필배원리，건립대불량측량구유로봉성적자괄응SRCKF 。기우STF적이론광가，채용자괄응SRCKF대체확전잡이만려파구건강근종자괄응SRCKF 。해산법겸구STF여자괄응SR-CKF적우점，재계통동시존재모형불학정성급불량측량시구유량호적려파성능。방진험증료소건산법적유효성。
To overcome problems that malfunctions in the measurement system lead to degradation of performance of strong tracking filter (STF)and inherent disadvantages of STF,an adaptive square-root cubature Kalman filter (SRCKF)algorithm is pro-posed .With innovation covariance matching techniques an adaptive SRCKF is built,which is insensitive to measurement malfunc-tions .Strong tracking adaptive SRCKF views STF as the basic theory framework and makes adaptive SRCKF to replace extended Kalman filter (EKF),so it has the advantages of STF and adaptive SRCKF .In case of model uncertainty of system and measure-ment malfunctions,the proposed algorithm has strong robustness and high accuracy .Simulation results show the effectiveness of the presented algorithm .