Results 151 to 160 of about 70,135 (188)

Distributed fusion incremental Kalman filter

2018 Chinese Control And Decision Conference (CCDC), 2018
In the actual application process, the impact of the surrounding environment, the error of the observation device, and the improper parameter selection usually yield the system error. The incremental Kalman filter can effectively solve the state estimation problem for the systems under poor observation condition.
Mandi Wang, Guangming Yan, Xiaojun Sun
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Distributed Kalman Filter using fast polynomial filter

2011 IEEE International Symposium of Circuits and Systems (ISCAS), 2011
Distributed estimation algorithms have received a lot of attention in the past few years, particularly in the fusion framework of Wireless Sensor Network (WSN). Distributed Kalman Filter (DKF) for WSN is one of the most fundamental distributed estimation algorithms for scalable wireless sensor fusion.
A. Abdelgawad, M. Bayoumi
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The Hypothesizing Distributed Kalman Filter

2012 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), 2012
This paper deals with distributed information processing in sensor networks. We propose the Hypothesizing Distributed Kalman Filter that incorporates an assumption of the global measurement model into the distributed estimation process. The procedure is based on the Distributed Kalman Filter and inherits its optimality when the assumption about the ...
Reinhardt, M., Noack, B., Hanebeck, U. D.   +2 more
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Proposed Distributed Kalman Filter

2012
In this chapter, the DKF problem is addressed by reducing it into a dynamic consensus problem in term of weighted average estimates matrix that can be viewed as data fusion problem. We have presented a Distributed Kalman Filter based on polynomial filter to accelerate the distributed average consensus in the static network topologies.
Ahmed Abdelgawad, Magdy Bayoumi
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Distributed Kalman Filtering With Adaptive Communication

IEEE Control Systems Letters
This work proposes an adaptive event-triggered communication framework for distributed state estimation in sensor networks, enabling each node to self-adapt its transmission rule while maintaining a desired average rate and complying with an upper bound on individual transmission rates.
Daniela Selvi, Giorgio Battistelli
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Real‐time Kalman filtering based on distributed measurements

International Journal of Robust and Nonlinear Control, 2012
SUMMARYA kind of real‐time Kalman filtering problem is discussed for systems with distributed multichannel measurements. Recursive filters are presented for two cases with correlated and uncorrelated measurement noises. An optimal algorithm is constructed using projection theory in Hilbert space according to a first‐come‐first‐served scheme.
Lam, J, Cui, P, Zhang, H, Ma, L
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Distributed Kalman Filter with Embedded Consensus Filters

Proceedings of the 44th IEEE Conference on Decision and Control, 2006
The problem of distributed Kalman filtering (DKF) for sensor networks is one of the most fundamental distributed estimation problems for scalable sensor fusion. This paper addresses the DKF problem by reducing it to two separate dynamic consensus problems in terms of weighted measurements and inverse-covariance matrices.
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Convergence results in distributed Kalman filtering

2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011
The paper studies the convergence properties of the estimation error processes in distributed Kalman filtering for potentially unstable linear dynamical systems. In particular, it is shown that, in a weakly connected communication network, there exist (randomized) gossip based information dissemination schemes leading to a stochastically bounded ...
Soummya Kar, Shuguang Cui, H. Vincent Poor, Jose M. F. Moura   +3 more
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Scalable distributed Kalman filtering through consensus

2008 IEEE International Conference on Acoustics, Speech and Signal Processing, 2008
Kalman filtering is a classical technique with a number of potential distributed applications in sensor networks. In this paper we consider a specific algorithm for distributed Kalman filtering proposed recently by Olfati-Saber [Olfati-Saber, 2005 ].
Shrut Kirti, Anna Scaglione
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Stability of distributed extended Kalman filters

2017 22nd International Conference on Digital Signal Processing (DSP), 2017
The need for faster and more robust parameter estimates in the smart grid, together with the growth in multi-sensor distributed measurements has motivated the development of distributed extended Kalman filtering (EKF) algorithms. However, fundamental theoretical insights about the convergence and stability of these distributed extended Kalman filtering
Sithan Kanna, Danilo P. Mandic
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