Results 11 to 20 of about 48,416 (251)
Sensors, 2008 This paper proposes a new distributed Kalman filtering fusion with random state transition and measurement matrices, i.e., random parameter matrices Kalman filtering.
Donghua Wang +5 more
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Distributed Kalman filtering: a bibliographic review
IET Control Theory & Applications, 2013 In recent years, a compelling need has arisen to understand the effects of distributed information structures on estimation and filtering. In this study, a bibliographical review on distributed Kalman filtering (DKF) is provided. The study contains a classification of different approaches and methods involved to DKF.
Magdi S. Mahmoud, Haris M. Khalid
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Systems Science & Control Engineering, 2020 In this paper, some recent results on the distributed filtering, estimation and fusion algorithms for nonlinear systems with communication constraints are reviewed.
Zhibin Hu, Jun Hu, Guang Yang
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IEEE Access, 2020 Distributed position and orientation system (POS) plays an important role in the fields of aerial remote sensing, which serves the sensors by precise motion information.
Bo Wang, Wen Ye, Yanhong Liu
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Sensors, 2023 In the distributed information fusion of wireless sensor networks (WSNs), the filtering accuracy is commonly negatively correlated with energy consumption.
Chunxi Yang +3 more
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Distributed Kalman-filtering: Distributed optimization viewpoint [PDF]
2019 IEEE 58th Conference on Decision and Control (CDC), 2019 We consider the Kalman-filtering problem with multiple sensors which are connected through a communication network. If all measurements are delivered to one place called fusion center and processed together, we call the process centralized Kalman-filtering (CKF).
Ryu, Kunhee, Back, Juhoon
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A Bayesian approach to distributed optimal filtering over a ring network
Measurement: Sensors, 2021 This paper is concerned with the state estimation over a sensor network. Distributed estimation algorithms enable us to estimate the system state using the information from other sensors, even when the state is not completely observable from some sensors.
Akihiro Tsuji +2 more
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Distributed Kalman Filtering: Consensus, Diffusion, and Mixed [PDF]
2018 IEEE Conference on Control Technology and Applications (CCTA), 2018 A distributed Kalman filtering technique is developed for tracking state-space processes via sensor networks. Considering the optimal solution to multi-agent sequential filtering of linear Gaussian state-space processes, that is the centralized Kalman filter, this work focuses on decomposing and distributing the operation of the centralized Kalman ...
Talebi, Sayed Pouria, Werner, Stefan
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Distributed nonlinear Kalman filter with communication protocol [PDF]
Information Sciences, 2020 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hilton Tnunay +2 more
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Distributed Kalman Filtering Under Model Uncertainty [PDF]
IEEE Transactions on Control of Network Systems, 2020 We study the problem of distributed Kalman filtering for sensor networks in the presence of model uncertainty. More precisely, we assume that the actual state-space model belongs to a ball, in the Kullback-Leibler topology, about the nominal state-space model and whose radius reflects the mismatch modeling budget allowed for each time step.
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