Results 11 to 20 of about 202,753 (224)
Privacy-Preserving Distributed Kalman Filtering
IEEE Transactions on Signal Processing, 2022 Distributed Kalman filtering techniques enable agents of a multiagent network to enhance their ability to track a system and learn from local cooperation with neighbors.
Ashkan Moradi +3 more
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Distributed Kalman Filtering Under Model Uncertainty [PDF]
IEEE Transactions on Control of Network Systems, 2019 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 ...
Mattia Zorzi
semanticscholar +4 more sources
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 ...
Kunhee Ryu, J. Back
semanticscholar +4 more sources
Distributed receding horizon Kalman filter [PDF]
49th IEEE Conference on Decision and Control (CDC), 2010 In this paper a distributed version of the Kalman filter is proposed. In particular, the estimation problem is reduced to the optimization of a cost function that depends on the system dynamics and the latest output measurements and state estimates which is distributed among the local subsystems by means of dual decomposition.
Maestre J.M., Giselsson P., Rantzer A.
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Frontiers in Robotics and AI, 2023 In this paper, a distributed cooperative filtering strategy for state estimation has been developed for mobile sensor networks in a spatial–temporal varying field modeled by the advection–diffusion equation.
Ziqiao Zhang +4 more
doaj +1 more source
Distributed Kalman estimation with decoupled local filters [PDF]
Automatica, 2021 We study a distributed Kalman filtering problem in which a number of nodes cooperate without central coordination to estimate a common state based on local measurements and data received from neighbors. This is typically done by running a local filter at each node using information obtained through some procedure for fusing data across the network.
Marelli, Damian, Sui, Tianju, Fu, Minyue
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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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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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