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Gaussian mixture filter allowing negative weights and its application to positioning using signal strength measurements

机译:高斯混合滤波器,可实现负权重并将其应用于通过信号强度测量进行定位

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This paper proposes a novel Gaussian Mixture Filter (GMF) that allows components with negative weights. In the case of a ring-shaped likelihood function, the new filter keeps the number of components low by approximating the likelihood as a Gaussian mixture (GM) of two components, one with positive and the other with negative weight. In this article, the filter is applied to positioning with received signal strength (RSS) based range measurements. The filter is tested using simulated measurements, and the tests indicate that the new GMF outperforms the Extended Kalman Filter (EKF) in both accuracy and consistency.
机译:本文提出了一种新颖的高斯混合滤波器(GMF),它允许分量具有负权重。在环形似然函数的情况下,新滤波器通过将似然近似为两个分量的高斯混合(GM),一个分量为正,而另一个分量为负,将分量的数量保持为较低。本文将滤波器应用于基于接收信号强度(RSS)的距离测量的定位。使用模拟测量值对滤波器进行了测试,测试表明,新GMF在准确性和一致性方面均优于扩展卡尔曼滤波器(EKF)。

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