Multi‐sensor particle filtering with multi‐step randomly delayed measurements
Author:
Affiliation:
1. Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin People's Republic of China
2. School of Science Harbin Institute of Technology Shenzhen People's Republic of China
Publisher
Institution of Engineering and Technology (IET)
Subject
Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1049/smt2.12004
Reference23 articles.
1. Optimal Linear Estimators for Systems With Random Sensor Delays, Multiple Packet Dropouts and Uncertain Observations
2. Gaussian Smoothers for Nonlinear Systems With One-Step Randomly Delayed Measurements
3. Latency probability estimation of non‐linear systems with one‐step randomly delayed measurements
4. Alternative framework of the Gaussian filter for non‐linear systems with randomly delayed measurements and correlated noises;Zhao K.;IET Sci. Measurement Technol.,2018
5. Adaptive Kalman Filtering in Networked Systems With Random Sensor Delays, Multiple Packet Dropouts and Missing Measurements
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1. Multi-sensor fusion particle filtering for Boolean networks with multi-step randomly-delayed measurements;Neurocomputing;2023-08
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