Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Distributed online localization in sensor networks using a moving target
Proceedings of the 3rd international symposium on Information processing in sensor networks
Distributed particle filters for sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Correctness of Local Probability Propagation in Graphical Models with Loops
Neural Computation
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Distributed average consensus with least-mean-square deviation
Journal of Parallel and Distributed Computing
Broadcast gossip algorithms for consensus
IEEE Transactions on Signal Processing
Time-space-sequential distributed particle filtering with low-rate communications
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Detection and Tracking Using Particle-Filter-Based Wireless Sensor Networks
IEEE Transactions on Mobile Computing
Distributed target tracking using signal strength measurements by a wireless sensor network
IEEE Journal on Selected Areas in Communications - Special issue on simple wireless sensor networking solutions
Completely Distributed Particle Filters for Target Tracking in Sensor Networks
IPDPS '11 Proceedings of the 2011 IEEE International Parallel & Distributed Processing Symposium
Fully Distributed Algorithms for Convex Optimization Problems
SIAM Journal on Optimization
Loopy belief propagation as a basis for communication in sensor networks
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Wireless Personal Communications: An International Journal
Gaussian sum particle filtering
IEEE Transactions on Signal Processing
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
IEEE Transactions on Information Theory
Nonparametric belief propagation for self-localization of sensor networks
IEEE Journal on Selected Areas in Communications
Set-Membership Constrained Particle Filter: Distributed Adaptation for Sensor Networks
IEEE Transactions on Signal Processing
Distributed Clock Synchronization for Wireless Sensor Networks Using Belief Propagation
IEEE Transactions on Signal Processing
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In distributed target tracking for wireless sensor networks, agreement on the target state can be achieved by the construction and maintenance of a communication path, in order to exchange information regarding local likelihood functions. Such an approach lacks robustness to failures and is not easily applicable to ad-hoc networks. To address this, several methods have been proposed that allow agreement on the global likelihood through fully distributed belief consensus (BC) algorithms, operating on local likelihoods in distributed particle filtering (DPF). However, a unified comparison of the convergence speed and communication cost has not been performed. In this paper, we provide such a comparison and propose a novel BC algorithm based on belief propagation (BP). According to our study, DPF based on metropolis belief consensus (MBC) is the fastest in loopy graphs, while DPF based on BP consensus is the fastest in tree graphs. Moreover, we found that BC-based DPF methods have lower communication overhead than data flooding when the network is sufficiently sparse.