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Gaussian Process Gaussian Mixture PHD Filter for 3D Multiple Extended Target Tracking
Remote Sensing, 2023 This paper addresses the problem of tracking multiple extended targets in three-dimensional space. We propose the Gaussian process Gaussian mixture probability hypothesis density (GP-PHD) filter, which is capable of tracking multiple extended targets ...
Zhiyuan Yang +4 more
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Adaptive Maximum Correntropy Gaussian Filter Based on Variational Bayes [PDF]
Sensors, 2018 Guoqing Wang +2 more
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Gaussian filters for nonlinear filtering problems [PDF]
IEEE Transactions on Automatic Control, 2000 The most widely used filter to estimate the state of a nonlinear stochastic system from noisy observation data is the extended Kalman filter. However, if the nonlinearities are significant, its performance can be considerably improved as recent works by Alspace and Sorenson (1967, 1972), C. P. Fang, Julier and Uhlmann (1994, 1995) have shown.
Kazufumi Ito, Kaiqi Xiong
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A hybrid particle-ensemble Kalman filter for problems with medium nonlinearity.
PLoS ONE, 2021 A hybrid particle ensemble Kalman filter is developed for problems with medium non-Gaussianity, i.e. problems where the prior is very non-Gaussian but the posterior is approximately Gaussian. Such situations arise, e.g., when nonlinear dynamics produce a
Ian Grooms, Gregor Robinson
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IEEE Access, 2021 We present an approach which combines the sample regenerating particle filter (SRGPF) and unequal weight ensemble Kalman filter (UwEnKF) to obtain a more accurate forecast for nonlinear dynamic systems.
Xiao Li, Ai Jie Cheng, Hai Xiang Lin
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Sensors, 2022 In this paper, a novel form of the Gaussian filter, the Mittag–Leffler filter is presented. This new filter uses the Mittag–Leffler function in the probability-density function.
Ivo Petráš
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Split-Gaussian particle filter [PDF]
2015 23rd European Signal Processing Conference (EUSIPCO), 2015 Publication in the conference proceedings of EUSIPCO, Nice, France ...
Juho Kokkala, Simo Särkkä
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Adaptive federated filter for multi-sensor nonlinear system with cross-correlated noises.
PLoS ONE, 2021 This paper presents an adaptive approach to the federated filter for multi-sensor nonlinear systems with cross-correlations between process noise and local measurement noise.
Lijun Wang, Sisi Wang, Wenzhi Yang
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Sensing Tensors With Gaussian Filters [PDF]
IEEE Transactions on Information Theory, 2017 Sparse recovery from linear Gaussian measurements has been the subject of much investigation since the breaktrough papers \cite{CRT:IEEEIT06} and \cite{donoho2006compressed} on Compressed Sensing. Application to sparse vectors and sparse matrices via least squares penalized with sparsity promoting norms is now well understood using tools such as ...
Stéphane Chrétien, Tianwen Wei
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Wrapped Particle Filtering for Angular Data
IEEE Access, 2022 Particle filtering is probably the most widely accepted methodology for general nonlinear filtering applications. The performance of a particle filter critically depends on the choice of proposal distribution.
Guddu Kumar +4 more
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