针对加性噪声,提出了培养卡尔曼滤波器和正交卡尔曼滤波器的增广形式

Pengfei Li, Jianping Yu, Mingjie Wan, Jianjun Huang, Jingxiong Huang
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引用次数: 9

摘要

本文提出了正交卡尔曼滤波器(QKF)和立方卡尔曼滤波器(CKF)的增广形式,用于估计非线性动态系统。通过形成增广状态变量对QKF和CKF进行修正,将状态和噪声分量连接在一起,从而可以更好地利用过程噪声和测量噪声的影响来捕获奇阶矩信息。仿真结果表明增广形式比非增广形式具有更好的性能。此外,还比较了三种非线性滤波器在增广形式和非增广形式下的性能和执行时间。
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The augmented form of cubature Kalman filter and quadrature Kalman filter for additive noise
In this paper, the augmented forms of the quadrature Kalman filter (QKF) and cubature Kalman filter (CKF) are presented for estimating the nonlinear dynamic systems. The QKF and CKF are modified by forming an augmented state variable, which concatenates the state and noise components together, so that the effect of process and measurement noises can be used to better capture the odd-order moment information. The simulation results demonstrate the improved performance of the augmented form over the nonaugmented form. Besides, the performance and the execution time of the three kinds of nonlinear filters is also compared in the augmented form and nonaugmented form.
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