Results 1 to 10 of about 223,064 (315)
Covariance-tuned EKF resampling based particle filter
Signal processing in complex environments is a challenging issue in many applications. Recent studies show that variants of particle filters achieve significant performance in positioning and tracking applications under complex environments.
N. Ashok Kumar +2 more
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20 pages, 21 figures, https://www.youtube.com/watch?v ...
Ryuichi Ueda +2 more
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Particle Filtering: The Need for Speed [PDF]
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gustaf Hendeby +2 more
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Under the clutter background condition, the existing particle filter pre-detection tracking algorithm based on Probability Hypothesis Density (PHD) filtering is not accurate enough to estimate the number of targets in dense multi-objectives.
PEI Jiazheng +4 more
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In order to investigate the distribution characteristics of gas-particle two-phase flow in the diesel particulate filter in the capture process, a mathematical model of gas-particle two-phase flow for inside-and-outside filter had been established in the
Jianyu Li, Chunping Lu, Dongli Tan
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Stratified Particle Filter Monocular SLAM
This paper presents a solution to the problem of simultaneous localization and mapping (SLAM), developed from a particle filter, utilizing a monocular camera as its main sensor.
Pawel Slowak, Piotr Kaniewski
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Filtering via Simulation: Auxiliary Particle Filters [PDF]
This article analyses the recently suggested particle approach to filtering time series. We suggest that the algorithm is not robust to outliers for two reasons: the design of the simulators and the use of the discrete support to represent the sequentially updating prior distribution. Here we tackle the first of these problems.
Michael K Pitt, Neil Shephard
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Optimal Intermittent Particle Filter
13 pages, 7 figures, 3 ...
Antoine Aspeel +3 more
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The Coordinate Particle Filter - a novel Particle Filter for high dimensional systems [PDF]
Parametric filters, such as the Extended Kalman Filter and the Unscented Kalman Filter, typically scale well with the dimensionality of the problem, but they are known to fail if the posterior state distribution cannot be closely approximated by a density of the assumed parametric form.
Manuel Wüthrich +4 more
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Improved Rao-Blackwellized Particle Filter by Particle Swarm Optimization
The Rao-Blackwellized particle filter (RBPF) algorithm usually has better performance than the traditional particle filter (PF) by utilizing conditional dependency relationships between parts of the state variables to estimate.
Zeng-Shun Zhao +8 more
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