Results 151 to 160 of about 8,181 (194)

Truncated unscented particle filter

Proceedings of the 2011 American Control Conference, 2011
The problem of state estimation of nonlinear stochastic dynamic systems with nonlinear inequality constraints is treated. The paper focuses on a particle filtering approach, which provides an estimate of the state in the form of a probability density function.
Ondrej Straka, Jindrich Duník, Miroslav Simandl   +2 more
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Robust Adaptive Unscented Particle Filter

International Journal of Intelligent Mechatronics and Robotics, 2013
This paper presents a new robust adaptive unscented particle filtering algorithm by adopting the concept of robust adaptive filtering to the unscented particle filter. In order to prevent particles from degeneracy, this algorithm adaptively determines the equivalent weight function according to robust estimation and adaptively adjusts the adaptive ...
Li Xue, Shesheng Gao, Yongmin Zhong
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Unscented Particle Double Layer Filter

2018 21st International Conference on Information Fusion (FUSION), 2018
The Particle filter (PF) provides a general numerical tool to deal with the non-Gaussian filtering problems, but it has the particle depletion problem and so on. The unscented particle filter (UPF) can solve the problem of particle depletion, but it has the computationally intensive problem and so on.
Feng Yang 0001, Litao Zheng, Wentong Li 0001, Yongting Wang, Pengxiang Wang 0001   +4 more
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The ensemble unscented particle filter

2011 2nd International Conference on Intelligent Control and Information Processing, 2011
The particle filter is a Monte Carlo method that allows us to treat any probability distribution, nonlinear and non-Gaussian. However the choice of the proposal distribution is the most critical problem. Unscented particle filter (UPF) uses UKF to generate and propagate the Gaussian distribution which provides a better approximation to the optimal ...
Xi Qing Wei, Xiu Jie Zhang, Han Yu, Shen Min Song   +3 more
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Unscented Kalman Filter and Particle Filter for Chaotic Synchronization

APCCAS 2006 - 2006 IEEE Asia Pacific Conference on Circuits and Systems, 2006
The first and foremost step in developing a chaotic communication system is to establish synchronization of the chaotic systems/maps at the transmitter and receiver. Extended Kalman filter (EKF) is a widely studied nonlinear observer for chaotic synchronization.
Ajeesh P. Kurian, Sadasivan Puthusserypady   +1 more
openaire   +1 more source

Improved auxiliary and Unscented Particle Filter variants

52nd IEEE Conference on Decision and Control, 2013
This paper proposes some modifications to the Auxiliary Particle Filter and the Unscented Particle Filter. For the APF, based on some error bound considerations it is suggested that the auxiliary weights are taken into account not proportionally but nonlinearly.
Alexandros C. Charalampidis, George P. Papavassilopoulos   +1 more
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Improved unscented Kalman particle filter

2010 IEEE International Conference on Mechatronics and Automation, 2010
In order to improve tracking estimation accuracy of existing unscented Kalman particle filter (UPF), an improved particle filter algorithm based on iterative measurement update UKF is proposed. The algorithm uses maximum posteriori estimate of iterative unscented Kalman filter as the important density function of the particle filter and amends the ...
Guo-hui Li, Ya-an Li, Hong Yang, Lin Cui
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The Semi-Iterative Unscented Particle Filtering

2009 International Workshop on Intelligent Systems and Applications, 2009
Particle filtering algorithm has been widely used in solving nonlinear/non Gaussian filtering problems. In this paper, a novel filtering method –mixed unscented particle filtering (MUPF) for nonlinear dynamic systems is proposed. MUPF mainly includes two steps.
Aixia Wang, Jingjiao Li, Aiyun Yan
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An unscented particle filter for GMTI tracking

2004 IEEE Aerospace Conference Proceedings (IEEE Cat. No.04TH8720), 2004
Ground moving target indicator (GMTI) tracking is often carried out using extended Kalman filters, as in the variable-structure interacting multiple-model (VS-IMM) filter. In some scenarios, however, this is considered to be inadequate. It has been shown that in this case, a particle filter can give better performance.
O. Payne, A. Marrs
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Unscented Particle Filters with Refinement Steps for UAV Pose Tracking

Journal of Intelligent & Robotic Systems, 2021
Particle Filters (PFs) have been successfully employed for monocular 3D model-based tracking of rigid objects. However, these filters depend on the computation of importance weighs that use sub-optimal approximations to the likelihood function. In this paper, we propose to enrich the filter with additional refinement steps to abridge its sub-optimality.
Nuno Pessanha Santos, Victor Sousa Lobo, Alexandre Bernardino   +2 more
openaire   +1 more source