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Square Root Cubature Kalman Filter-Kalman Filter Algorithm for Intelligent Vehicle Position Estimate

机译:Square Root Cubature Kalman滤波器-Kalman滤波器算法估算智能车辆位置

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A new filtering algorithm, adaptive square root cubature Kalman filter-Kalman filter (SRCKF-KF) is proposed to reduce the problems of amount of calculation, complex formula-transform, low accuracy, poor convergence or even divergence. The method uses cubature Kalman filter (CKF) to estimate the nonlinear states of model while its linear states are estimated by the Kalman filter (KF). The simulation and practical experiment results show that, compared to the extended Kalman filter (EKF) and unscented Kalman filter (UKF).The modified filter not only enhances the numerical stability, guarantees positive definiteness of the state covariance, but also increases accuracy, which has high practicability.
机译:提出了一种新的过滤算法,Adaptive Square Root Cubature Kalman滤波器-Kalman滤波器(SRCKF-KF),以减少计算量,复杂的式变换,低精度,收敛差或甚至发散的问题。该方法使用Cubature Kalman滤波器(CKF)来估计模型的非线性状态,而Kalman滤波器(KF)估计其线性状态。仿真和实验结果表明,与扩展卡尔曼滤波器(EKF)和Unscented Kalman滤波器(UKF)相比。改进的过滤器不仅提高了数值稳定性,保证了国家协方差的积极肯定,还可以提高精度具有很高的实用性。

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