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Distributed Sequential Estimation in Asynchronous Wireless Sensor Networks
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DOI：10.1109/LSP.2015.2448601.png)
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Abstract
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We propose a distributed sequential estimation scheme for wireless sensor networks with asynchronous measurements. Our scheme combines the prediction and update steps of a Bayesian filter (for time alignment and recursive state estimation) with a fusion rule (for intersensor fusion using local communication). We also propose a reduced-complexity implementation using particle filtering and Gaussian mixture approximations, and an estimator of the delays resulting from processing and communication. Simulations for a target tracking problem demonstrate the good performance of our scheme.
Keywords:
Asynchronous measurements
data fusion
distributed particle filter
distributed state estimation
target tracking
wireless sensor network
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