Results 261 to 270 of about 8,582 (299)

Target existence probability in the distributed Kalman filter

2013 Workshop on Sensor Data Fusion: Trends, Solutions, Applications (SDF), 2013
In this paper, the target existence probability for a single target in clutter is derived. More specifically, the paper considers target existence in the distributed Kalman filter. First, a conceptual solution is derived explicitly for a two-sensor case, and second a moment-matching approximation is performed, which enables computational tractability ...
Daniel Svensson, Felix Govaers, Martin Ulmke, Wolfgang Koch 0001   +3 more
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Distributed minimum error entropy Kalman filter

Information Fusion, 2023
Bei Peng
exaly   +2 more sources

Performance analysis of trace proximity based distributed Kalman filter

Signal Processing
This paper analyzes the performance of the distributed Kalman filter based on trace proximity criterion and neighboring-node measurements (TPCNM) proposed in Liu et al.
Shuoyu Wang
exaly   +2 more sources

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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Distributed Kalman Filtering Through Trace Proximity

IEEE Transactions on Automatic Control, 2022
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Wei Liu 0079, Peng Shi 0001, Shuoyu Wang
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A distributed Kalman filter with global covariance

Proceedings of the 2011 American Control Conference, 2011
Most distributed Kalman filtering (DKF) algorithms for sensor networks calculate a local estimate of the global state-vector in each node. An important challenge within distributed estimation is that all sensors in the network contribute to the local estimate in each node.
Sijs, J., Lazar, M.
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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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Distributed Kalman Filtering With Adaptive Communication

IEEE Control Systems Letters
This letter 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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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, José M. F. Moura   +3 more
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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.
Ahmed Abdelgawad 0001, Magdy A. Bayoumi
openaire   +1 more source