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Nonlinear filtering for a kind of divisible systems

机译:一类可整系统的非线性滤波

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摘要

For the nonlinear system whose state equation is composed of linear part and non-linear part, a novel nonlinear filter design method combined with Kalman Filter and Unscented Kalman filtering (UKF) is proposed in this paper. The algorithm divides the system into the linear sub-system and the non-linear sub-system. The optimal Kalman filter is used for the linear sub-system, on this basis, an improved UKF is utilized for the non-linear sub-system, in the sequential fusion frame. Compared with the traditional unscented Kalman filtering method, the optimality of the proposed methodfor the linear sub-system can be ensured. Therefore, the accuracy of the proposed method is superior to the traditional UKF. And the simulation results show that the improved algorithm estimation value is closer to the true value, and the filtering performance of the nonlinear system is improved.
机译:针对状态方程由线性部分和非线性部分组成的非线性系统,提出了一种结合卡尔曼滤波和无味卡尔曼滤波(UKF)的非线性滤波器设计方法。该算法将系统分为线性子系统和非线性子系统。最优卡尔曼滤波器用于线性子系统,在此基础上,在顺序融合帧中将改进的UKF用于非线性子系统。与传统的无味卡尔曼滤波方法相比,该方法对于线性子系统的最优性。因此,所提出方法的准确性优于传统UKF。仿真结果表明,改进后的算法估计值更接近真实值,提高了非线性系统的滤波性能。

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