A Gaussian Uniform Mixture Model for Robust Kalman Filtering

Brunot Mathieu

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A Gaussian Uniform Mixture Model for Robust Kalman Filtering

机译：高斯均匀混合模型，适用于鲁棒卡尔曼滤波

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This article presents a Kalman-type recursive estimator for discrete-time systems with a measurement noise modeled by a Gaussian-uniform mixture. The objective is to deal with data containing outliers that degrade the performance of the regular Kalman filter. The proposed non-Gaussian noise model takes into account the reliability of the measurement with respect to erroneous data. The Kalman-type estimator is based on Masreliez's formulation which copes with non-Gaussian noise models. Results in different simulated conditions are displayed to evaluate the performance of the newly-presented algorithm and to compare it to state-of-art alternatives.

机译：本文提出了一种用于离散时间系统的卡尔曼型递归估计器，其具有由高斯均匀混合物建模的测量噪声。目标是处理包含异常值的数据，从而降低常规卡尔曼滤波器的性能。所提出的非高斯噪声模型考虑了关于错误数据测量的可靠性。卡尔曼型估计器基于Masreliez的配方，该配方与非高斯噪声模型一起应对。结果显示不同的模拟条件以评估新呈现的算法的性能，并将其与最先进的替代方案进行比较。

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来源
《IEEE Transactions on Aerospace and Electronic Systems》 |2020年第4期|2656-2665|共10页
作者
Brunot Mathieu;
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作者单位

Off Natl Etud & Rech Aerosp F-31000 Toulouse France;

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原文格式 PDF
正文语种 eng
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关键词
Kalman filters; Noise measurement; Jacobian matrices; Mixture models; Reliability theory; Instruments; Bayesian estimation; Kalman filters (KFs); mixture models; noise robustness;

机译：卡尔曼过滤器;噪声测量;雅各比矩阵;混合模型;可靠性理论;仪器;贝叶斯估计;卡尔曼滤镜（KFS）;混合模型;噪音稳健;

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专利

1. Robust Kalman Filters Based on Gaussian Scale Mixture Distributions With Application to Target Tracking [J] . Huang Yulong, Zhang Yonggang, Shi Peng, IEEE Transactions on Systems, Man, and Cybernetics . 2019,第10期

机译：基于高斯尺度混合分布的鲁棒卡尔曼滤波器及其在目标跟踪中的应用
2. Comparing the adaptive Gaussian mixture filter with the ensemble Kalman filter on synthetic reservoir models [J] . Andreas S. Stordal, Randi Valestrand, Hans Arnfinn Karlsen, Computational Geosciences . 2012,第2期

机译：在合成油藏模型中将自适应高斯混合滤波器与集成卡尔曼滤波器进行比较
3. Multimodal ensemble Kalman filtering using Gaussian mixture models [J] . Laura Dovera, Ernesto Delia Rossa Computational Geosciences . 2011,第2期

机译：使用高斯混合模型的多峰集成卡尔曼滤波
4. Robust Comparison of Simultaneous EEG Recordings Using Kalman Filters and Gaussian Mixture Models [C] . Niels VON STEIN, Jonas SCHULTE-COERNE, Stephan M. JONAS, Health Informatics Meets Digital Health Conference. . 2019

机译：使用Kalman滤波器和高斯混合模型的同时EEG录制的鲁棒比较
5. Ensemble Kalman filter method for Gaussian and non-Gaussian priors. [D] . Zhao, Yong. 2008

机译：高斯先验和非高斯先验的集合卡尔曼滤波方法。
6. Inferring trial-to-trial excitatory and inhibitory synaptic inputs from membrane potential using Gaussian mixture Kalman filtering [O] . M. Lankarany, W.-P. Zhu, M. N. S. Swamy, 2013

机译：使用高斯混合卡尔曼滤波从膜电位推断试验至试验的兴奋性和抑制性突触输入
7. A Gaussian Uniform Mixture Model for Robust Kalman Filtering [O] . Mathieu Brunot 2020

机译：高斯均匀混合模型，适用于鲁棒卡尔曼滤波
8. Robust Filtering and Smoothing via Gaussian Mixtures [R] . Agee, W. S., Dunn, B. A. 1980

机译：通过高斯混合的鲁棒滤波和平滑

A Gaussian Uniform Mixture Model for Robust Kalman Filtering

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