Results 11 to 20 of about 241,859 (276)
Underwater Geomagnetic Localization Based on Adaptive Fission Particle-Matching Technology
Journal of Marine Science and Engineering, 2023 The geomagnetic field constitutes a massive fingerprint database, and its unique structure provides potential position correction information. In recent years, particle filter technology has received more attention in the context of robot navigation ...
Huapeng Yu +5 more
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Multilevel Particle Filters [PDF]
SIAM Journal on Numerical Analysis, 2017 In this paper the filtering of partially observed diffusions, with discrete-time observations, is considered. It is assumed that only biased approximations of the diffusion can be obtained, for choice of an accuracy parameter indexed by $l$. A multilevel estimator is proposed, consisting of a telescopic sum of increment estimators associated to the ...
Jasra, Ajay +3 more
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Feedback Particle Filter [PDF]
IEEE Transactions on Automatic Control, 2013 A new formulation of the particle filter for nonlinear filtering is presented, based on concepts from optimal control, and from the mean-field game theory. The optimal control is chosen so that the posterior distribution of a particle matches as closely as possible the posterior distribution of the true state given the observations. This is achieved by
Yang, Tao +2 more
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A Genetic Optimization Resampling Based Particle Filtering Algorithm for Indoor Target Tracking
Remote Sensing, 2021 In indoor target tracking based on wireless sensor networks, the particle filtering algorithm has been widely used because of its outstanding performance in coping with highly non-linear problems.
Ning Zhou +3 more
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Tempered Particle Filtering [PDF]
Finance and Economics Discussion Series, 2016 The accuracy of particle filters for nonlinear state-space models crucially depends on the proposal distribution that mutates time t-1 particle values into time t values. In the widely-used bootstrap particle filter this distribution is generated by the state-transition equation.
Edward Herbst, Frank Schorfheide
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A GENERIC PROBABILISTIC MODEL AND A HIERARCHICAL SOLUTION FOR SENSOR LOCALIZATION IN NOISY AND RESTRICTED CONDITIONS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 A generic probabilistic model, under fundamental Bayes’ rule and Markov assumption, is introduced to integrate the process of mobile platform localization with optical sensors.
S. Ji, S. Ji, X. Yuan
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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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A weighted likelihood criteria for learning importance densities in particle filtering
EURASIP Journal on Advances in Signal Processing, 2018 Selecting an optimal importance density and ensuring optimal particle weights are central challenges in particle-based filtering. In this paper, we provide a two-step procedure to learn importance densities for particle-based filtering.
Muhammad Javvad ur Rehman +2 more
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Semi-independent resampling for particle filtering [PDF]
, 2017 Among Sequential Monte Carlo (SMC) methods,Sampling Importance Resampling (SIR) algorithms are based on Importance Sampling (IS) and on some resampling-based)rejuvenation algorithm which aims at fighting against weight degeneracy.
Desbouvries, François +3 more
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Nonlinear Compressive Particle Filtering [PDF]
, 2013 Many systems for which compressive sensing is used today are dynamical. The common approach is to neglect the dynamics and see the problem as a sequence of independent problems. This approach has two disadvantages. Firstly, the temporal dependency in the
Ohlsson, Henrik +2 more
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