WSEAS TRANSACTIONS on SYSTEMS
ICAI'09 Proceedings of the 10th WSEAS international conference on Automation & information
Time series identification methodology using wireless sensor networks
ISPRA'10 Proceedings of the 9th WSEAS international conference on Signal processing, robotics and automation
Implementing time series identification methodology using wireless sensor networks
WSEAS Transactions on Computers
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Envisioned applications of wireless sensor networks (WSNs) include surveillance, monitoring and tracking tasks. These motivate well decentralized estimation and smoothing of deterministic and (non)stationary random signals using (possibly correlated) observations collected across distributed sensors. In this talk we present state-of-the-art algorithms for consensus-based distributed estimation using ad hoc WSNs where sensors communicate over single-hop noisy links. The novel framework reformulates basic estimation criteria such as least-squares, maximum-likelihood, maximum a posteriori, and linear mean-square error, as decomposable, constrained, convex optimization problems that are amenable to distributed solutions. The resultant distributed estimators are provably convergent to their centralized counterparts and robust to communication noise. Besides stationary, the framework encompasses adaptive filtering and smoothing of non-stationary signals through distributed LMS and Kalman filtering.