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首页> 外文期刊>IEEE Transactions on Signal Processing >Square-Root Quadrature Kalman Filtering
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Square-Root Quadrature Kalman Filtering

机译:平方根正交卡尔曼滤波

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摘要

The quadrature Kalman filter (QKF) is a recursive, nonlinear filtering algorithm developed in the Kalman filtering framework. It computes the mean and covariance of all conditional densities using the Gauss–Hermite quadrature rule. In this correspondence, we develop a square-root extension of the quadrature Kalman filter using matrix triangularizations. The square-root quadrature Kalman filter (SQKF) propagates the mean and the square root of the covariance. Although equivalent to the QKF algebraically, the SQKF exhibits excellent numerical characteristics, but at the expense of increased computational complexity. We also present possible refinements of the generic SQKF.
机译:正交卡尔曼滤波器(QKF)是在卡尔曼滤波框架中开发的递归非线性滤波算法。它使用高斯-赫姆特正交规则计算所有条件密度的均值和协方差。在这种对应关系中,我们使用矩阵三角化方法开发了正交卡尔曼滤波器的平方根扩展。平方根正交卡尔曼滤波器(SQKF)传播协方差的均值和平方根。尽管在代数上等同于QKF,但SQKF具有出色的数值特性,但以增加的计算复杂性为代价。我们还介绍了通用SQKF的可能改进。

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