Particle filter with one-step randomly delayed measurements and unknown latency probability

DOI10.1080/00207721.2015.1056272zbMath1333.93246OpenAlexW1756498584MaRDI QIDQ2795125

Lin Zhao, Yong-Gang Zhang, Ning Li, Yu-Long Huang

Publication date: 18 March 2016

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207721.2015.1056272

zbMATH Keywords

state estimationparticle filtermaximum likelihood criterionrandomly delayed measurementsidentification of latency probability

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Nonlinear systems in control theory (93C10) Discrete-time control/observation systems (93C55) Estimation and detection in stochastic control theory (93E10)

Related Items (7)

Risk sensitive filtering with randomly delayed measurements ⋮ Detection-estimation strategies for delayed systems with unavailable packet sequence ⋮ Particle filter with Markovian packet dropout and time delay ⋮ Bayesian filter for nonlinear systems with randomly delayed and lost measurements ⋮ Particle filtering for a class of cyber-physical systems under round-robin protocol subject to randomly occurring deception attacks ⋮ Particle Smoother for Nonlinear Systems With One‐Step Randomly Delayed Measurements ⋮ Cauchy kernel-based maximum correntropy Kalman filter

Cites Work

• Unnamed Item
• System identification of nonlinear state-space models
• Digital synthesis of non-linear filters
• Unscented filtering algorithm using two-step randomly delayed observations in nonlinear systems
• Design and implementation of Gaussian filter for nonlinear system with randomly delayed measurements and correlated noises
• Extended and unscented filtering algorithms using one-step randomly delayed observations
• Gaussian filter for nonlinear systems with one-step randomly delayed measurements
• Robust maximum-likelihood estimation of multivariable dynamic systems
• Linear estimation based on covariances for networked systems featuring sensor correlated random delays
• Particle filter for state estimation of jump Markov nonlinear system with application to multi-targets tracking
• Gain-Constrained Recursive Filtering With Stochastic Nonlinearities and Probabilistic Sensor Delays
• Particle filtering-based fault detection in non-linear stochastic systems
• Optimal linear estimators for systems with multiple random measurement delays and packet dropouts
• Maximum-likelihood parameter estimation of bilinear systems
• Unscented Kalman Filter: Aspects and Adaptive Setting of Scaling Parameter
• Gaussian Smoothers for Nonlinear Systems With One-Step Randomly Delayed Measurements
• A survey of convergence results on particle filtering methods for practitioners
• Gaussian particle filtering
• Gaussian sum particle filtering

This page was built for publication: Particle filter with one-step randomly delayed measurements and unknown latency probability