Information fusion for wireless sensor networks: Methods, models, and classifications
ACM Computing Surveys (CSUR)
Information fusion in wireless sensor networks
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Data fusion and topology control in wireless sensor networks
WSEAS Transactions on Signal Processing
Proceedings of the 12th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Refining inaccurate sensor positions using target at unknown location
Signal Processing
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This paper presents a source localization algorithm based on the source signal's time-of-arrival (TOA) at sensors that are not synchronized with one another or the source. The proposed algorithm estimates source positions using a window of TOA measurements which, in effect, creates a virtual sensor array. Based on a Gaussian noise model, maximum likelihood estimates (MLE) for the source position and displacement are obtained. Performance issues are addressed by evaluating the Cramer-Rao lower bound and considering the virtual sensor array's geometric properties. To track the source trajectory from the TOA measurement, which is a nonlinear function of source position and displacement, this localization algorithm is combined with the extended Kalman filter (EKF) and the unscented Kalman filter, resulting in good tracking performance