Journal ArticleDOI
Distributed consensus extended Kalman filter: a variance-constrained approach
Reads0
Chats0
TLDR
In this paper, a distributed extended Kalman filter (EKF) is developed for each node to guarantee an optimised upper bound on the state estimation error covariance despite consensus terms and linearisation errors.Abstract:
This study is concerned with the distributed state estimation problem for non-linear systems over sensor networks. By using the strategy of consensus on prior estimates, a distributed extended Kalman filter (EKF) is developed for each node to guarantee an optimised upper bound on the state estimation error covariance despite consensus terms and linearisation errors. The Kalman gain matrix is derived for each node by solving two Riccati-like difference equations. It is shown that the estimation error is bounded in mean square under certain conditions. The effectiveness of the proposed filter is evaluated on an indoor localisation of a mobile robot with visual tracking systems.read more
Citations
More filters
Journal ArticleDOI
Distributed estimation over a low-cost sensor network: a review of state-of-the-art
TL;DR: A comprehensive review of the state-of-the-art solutions in the domain of distributed estimation over a low-cost sensor network, exploring their characteristics, advantages, and challenging issues is presented.
Journal ArticleDOI
Event-triggered cooperative unscented Kalman filtering and its application in multi-UAV systems
TL;DR: This paper proposes a novel consensus-based distributed unscented Kalman filtering algorithm with event-triggered communication mechanisms that can significantly reduce unnecessary data transmissions and hence save communication energy consumption and alleviate the communication burden.
Journal ArticleDOI
Distributed extended Kalman filter with nonlinear consensus estimate
TL;DR: A new nonlinear consensus protocol with polynomial form is proposed to generate the consensus estimate and the Kalman gain matrix is determined for each node to guarantee an optimized upper bound on the state estimation error covariance despite consensus terms and linearization errors.
Journal ArticleDOI
Distributed Kalman Filtering Over Sensor Networks With Transmission Delays
TL;DR: A distributed Kalman filtering algorithm is designed to estimate the state based on a Kalman consensus filtering algorithm to solve the distributed state estimation problem over sensor networks.
Journal ArticleDOI
Consensus-Based Distributed Robust Filtering for Multisensor Systems With Stochastic Uncertainties
Fatemeh Rastgar,Mehdi Rahmani +1 more
TL;DR: Simulation results for a multisensor system with 100 nodes are presented to show the effectiveness and performance of the proposed CE-based distributed robust filtering approach.
References
More filters
Journal ArticleDOI
Consensus and Cooperation in Networked Multi-Agent Systems
TL;DR: A theoretical framework for analysis of consensus algorithms for multi-agent networked systems with an emphasis on the role of directed information flow, robustness to changes in network topology due to link/node failures, time-delays, and performance guarantees is provided.
Proceedings ArticleDOI
Distributed Kalman filtering for sensor networks
TL;DR: A continuous-time distributed Kalman filter that uses local aggregation of the sensor data but attempts to reach a consensus on estimates with other nodes in the network and gives rise to two iterative distributedKalman filtering algorithms with different consensus strategies on estimates.
Proceedings ArticleDOI
Distributed Kalman Filter with Embedded Consensus Filters
TL;DR: This paper shows that a central Kalman filter for sensor networks can be decomposed into n micro-Kalman filters with inputs that are provided by two types of consensus filters, and demonstrates that these filters can approximate these sums and give an approximate distributed Kalman filtering algorithm.
Proceedings ArticleDOI
Consensus Filters for Sensor Networks and Distributed Sensor Fusion
Reza Olfati-Saber,Jeff S. Shamma +1 more
TL;DR: This paper introduces a distributed filter that allows the nodes of a sensor network to track the average of n sensor measurements using an average consensus based distributed filter called consensus filter.
Journal ArticleDOI
Stochastic stability of the discrete-time extended Kalman filter
TL;DR: It is shown that the estimation error remains bounded if the system satisfies the nonlinear observability rank condition and the initial estimation error as well as the disturbing noise terms are small enough.