五阶容积卡尔曼滤波算法及其应用
Fifth degree cubature Kalman filter algorithm and its application
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摘要: 容积卡尔曼滤波(CKF)是一种新型的非线性滤波方法,可获得优于扩展卡尔曼滤波(EKF)和无迹卡尔曼滤波(UKF)的滤波精度和滤波效率.但是,传统的CKF基于三阶容积准则而提出,因此滤波精度受到限制,为进一步提高CKF滤波性能,文中将容积准则由三阶扩展到五阶,采用两种不同容积点集选择方案,提出一种新型的五阶CKF算法.该算法可有效改善传统CKF在精度方面的理论局限,并有效改善一般五阶CKF计算量大的问题.机动目标跟踪仿真结果表明了新方法的有效性和可行性.Abstract: Cubature Kalman Filter(CKF) is one of new nonlinear filters, its accuracy and efficiency are better than Extended Kalman Filter(EKF) and Unscented Kalman Filter(UKF). But the traditional CKF was proposed based on third order cubature rule and the filter accuracy was restricted. So the spherical-radial cubature rule was expended from third order to fifth order, the fifth order cubature rule based on two kinds of cubature point was used, a new fifth order CKF was proposed. The restriction of traditional CKF in theoretic accuracy was improved by the new fifth order CKF. The simulation results of the maneuvering target tracking show the validity and feasibility.