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Filters
Sample greedy gossip distributed Kalman filter
2020
Information Fusion
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Theoretical analysis on global convergence and uniform boundedness is also performed to investigate the characteristics of the proposed distributed Kalman filter. ...
A B S T R A C T This paper investigates the problem of distributed state estimation over a low-cost sensor network and proposes a new sample greedy gossip distributed Kalman filter. ...
Conclusions This paper proposed a distributed sample greedy gossip distributed Kalman filter over a sensor network. ...
doi:10.1016/j.inffus.2020.08.001
fatcat:pcun3jnrj5bcppkf43xijt4zce
A Generalized Kalman Consensus Filter for wide-area video networks
2011
IEEE Conference on Decision and Control and European Control Conference
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Distributed analysis of video captured by a large network of cameras has received significant attention lately. ...
Tracking moving targets is one of the most fundamental tasks in this regard and the well-known Kalman Consensus Filter (KCF) has been applied to this problem. ...
Generalized Kalman Consensus Filter for Multiple Targets This section discusses tracking of multiple targets in a distributed sensor network. ...
doi:10.1109/cdc.2011.6160333
dblp:conf/cdc/KamalDSFC11
fatcat:ip5pn3zqs5b4fdxmkxtamhn244
Randomized Consensus based Distributed Kalman Filtering over Wireless Sensor Networks
[article]
2018
arXiv
pre-print
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We provide the mean square convergence analysis of the proposed algorithm. ...
This paper is concerned with developing a novel distributed Kalman filtering algorithm over wireless sensor networks based on randomized consensus strategy. ...
Although the consensus based Kalman filtering algorithm is highly interesting, the proof of convergence and performance analysis are relatively difficult so far. It is still an open issue. ...
arXiv:1810.02531v1
fatcat:vgtthnqjtfby5cyosnvgembndi
Information-driven Fully Distributed Kalman Filter for Sensor Networks in Presence of Naive Nodes
[article]
2014
arXiv
pre-print
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We consider the distributed Kalman filtering problem for sensor networks where each node takes the measurement, communicates with its local neighbors, and updates its local estimate and estimation error ...
With some approximations in the derivation of the covariance matrix, we propose the Information-driven Fully Distributed Kalman filter (IFDKF), which is able to deal with the existence of naive nodes without ...
Conclusion We considered the distributed Kalman filtering problem of sensor networks where there exist naive nodes. ...
arXiv:1410.0411v1
fatcat:czzfbchcmjbozd3lrs3v4h7pga
A Survey on Distributed Filtering and Fault Detection for Sensor Networks
2014
Mathematical Problems in Engineering
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Finally, we conclude the paper by outlining future research challenges for distributed filtering and fault detection for sensor networks. ...
In particular, an urgent need has arisen to understand the effects of distributed information structures on filtering and fault detection in sensor networks. ...
Research Council (EPSRC) of the UK, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany. ...
doi:10.1155/2014/858624
fatcat:vekwbhavyngkreo3cqqomjkidi
Data-Aware Retrodiction for Asynchronous Harmonic Measurement in a Cyber-Physical Energy System
2016
Sensors
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This paper depicts a distributed measurement network for large-scale asynchronous harmonic analysis and exploits a nonlinear autoregressive model with exogenous inputs (NARX) network to reorder the out-of-sequence ...
OOSM algorithms based on the particle filter were developed following the Kalman filter-based methods. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/s16081316
pmid:27548171
pmcid:PMC5017481
fatcat:jwooxadqljfxboesojjnl5ttgm
Automatic online localization of nodes in an active sensor network
2004
IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004
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Localization of nodes within a sensing network is a fundamental requirement for many applications. ...
This paper proposes a method by which sensors self-localize based on their uncertain observations of other nodes in the network, using both Monte Carlo and Kalman Filtering techniques. ...
a gaussian, and used to seed a Kalman filter-based estimate of the camera location. ...
doi:10.1109/robot.2004.1302481
dblp:conf/icra/BrooksWM04
fatcat:hk6my2lfljbdll4ioulwe43e5a
Collaborative target tracking using distributed Kalman filtering on mobile sensor networks
2011
Proceedings of the 2011 American Control Conference
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We provide a formal stability analysis of continuous Kalman-Consensus filtering (KCF) algorithm on a mobile sensor network with a flocking-based mobility control model. ...
In this paper, we introduce a theoretical framework for coupled distributed estimation and motion control of mobile sensor networks for collaborative target tracking. ...
In this paper, we present a systematic analysis framework for mobile sensor networks with a flocking-based mobility control model that run a novel distributed Kalman filtering algorithm [8] for collaborative ...
doi:10.1109/acc.2011.5990979
fatcat:ujiymvsblzb5labkgczrf6mowe
VISNET: A distributed vision testbed
2008
2008 Second ACM/IEEE International Conference on Distributed Smart Cameras
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VISNET is a ten-node experimental camera network at UCSB used for various vision-related research. ...
The mission of VIS-NET is to provide an easy-to-use multi-node camera network to the vision research community at UCSB. ...
Now, the Kalman filter is ready for update. ...
doi:10.1109/icdsc.2008.4635707
dblp:conf/icdsc/QuinnMKNLM08
fatcat:hlwaq3kicbathisjwgblnjklxe
Coupled Distributed Estimation and Control for Mobile Sensor Networks
2012
IEEE Transactions on Automatic Control
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We provide a formal stability analysis of continuous Kalman-Consensus filtering (KCF) algorithm on a mobile sensor network with a flocking-based mobility control model. ...
In this paper, we introduce a theoretical framework for coupled distributed estimation and motion control of mobile sensor networks for collaborative target tracking. ...
In this paper, we present a systematic analysis framework for mobile sensor networks with a flocking-based mobility control model that run a novel distributed Kalman filtering algorithm [11] for collaborative ...
doi:10.1109/tac.2012.2190184
fatcat:rpii72m6xjeghcd3prhaty5qbm
Integrated predictive power control and dynamic channel assignment in mobile radio systems
2003
IEEE Transactions on Wireless Communications
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His general area of interest is in applying stochastic analysis, estimation and filtering, and other system theoretic techniques to applications in communication, control, and navigation systems. with ...
During the summer of 1999, he was with Mayflower Communications Corp., Billerica, MA, where he designed and implemented a navigation filter for a differential GPS system. ...
This proves the global stability of the network, on every channel, both in sense and in sense (with a linearized interference function), when the Kalman filters are at their steady-state. ...
doi:10.1109/twc.2003.817418
fatcat:vpe6udxti5gcph6rec2bbl4diu
Design and Implementation of Acoustic Sensing System for Online Early Fault Detection in Industrial Fans
2018
Journal of Sensors
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The kernel algorithm is based on an acoustic signal enhancement filter (ASEF) as well as an adaptive Kalman filter (AKF). ...
In addition, sensing and detection must rely on the use of sensors and sensing characteristics appropriate to various operational abnormalities. ...
Using the adaptive Kalman filter for analysis requires some parameter settings. ...
doi:10.1155/2018/4105208
fatcat:uoxjflj4dnftnevhb5mpip7eba
Application of Improved Deep Neural Network in Complex Chemical Soft Measurement
2018
Chemical Engineering Transactions
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After Kalman filtering equations were introduced, the algorithms of extended Kalman filter, volumetric Kalman filter and square root volumetric Kalman filter were optimized. ...
To improve the application effect of deep neural network in complex chemical soft measurement. ...
For the purpose of improvement, based on the linear Kalman filter, this paper presents an optimization algorithm for extended Kalman filter, volumetric Kalman filter and square root volumetric Kalman filter ...
doi:10.3303/cet1866160
doaj:07324f3f786b4205bd55311bef7032dc
fatcat:7o4npkw26zhyna5fh3czy466ma
Distributed Kalman Filter via Gaussian Belief Propagation
[article]
2008
arXiv
pre-print
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Other Versions
2008
2008 46th Annual Allerton Conference on Communication, Control, and Computing
unpublished
doi:10.1109/allerton.2008.4797617 fatcat:l6luxp222bfidaapc2lrq5bjoa
doi:10.1109/allerton.2008.4797617 fatcat:l6luxp222bfidaapc2lrq5bjoa
First, we show equivalence to computing one iteration of the Kalman filter. ...
Third, we discuss the relation to the Affine-scaling interior-point method and show it is a special case of Kalman filter. ...
distributively in a computer network. ...
arXiv:0810.1628v1
fatcat:wwt7ucywazhufnrwvcjzivza24
ARS: Adaptive Robust Synchronization for Underground Coal Wireless Internet of Things
2020
Sensors
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A clock synchronization framework that is based on Kalman filtering is first proposed, which can adaptively adjust the sampling period of each clock and reduce the communication overhead in single-hop ...
For multi-hop networks, the proposed scheme improves the accuracy by 12.56%. ...
Where KF stands for Kalman filter, case 1, case 2, and case 3 represent first-order Kalman Filter in single-hop networks, second-order Kalman filter in single-hop networks, and first-order Kalman filter ...
doi:10.3390/s20174981
pmid:32887451
pmcid:PMC7506929
fatcat:maatz4by6zbpfjqngxpxctscdm
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