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Kalman and smooth variable structure filters for robust estimation

机译:卡尔曼和平滑变结构滤波器用于鲁棒估计

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摘要

The extended Kalman filter (EKF) and the unscented Kalman filter (UKF) are among the most popular estimation methods. The smooth variable structure filter (SVSF) is a relatively new sliding mode estimator. In an effort to use the accuracy of the EKF and the UKF and the robustness of the SVSF, the filters have been combined, resulting in two new estimation strategies, called the EK-SVSF and the UK-SVSF, respectively. The algorithms were validated by testing them on a well-known target tracking computer experiment.
机译:扩展卡尔曼滤波器(EKF)和无味卡尔曼滤波器(UKF)是最受欢迎的估计方法。平滑可变结构滤波器(SVSF)是一个相对较新的滑模估计器。为了使用EKF和UKF的准确性以及SVSF的鲁棒性,已对滤波器进行了组合,从而产生了两种新的估计策略,分别称为EK-SVSF和UK-SVSF。通过在著名的目标跟踪计算机实验中对其进行测试来验证算法。

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