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Robust Target Localization From Binary Decisions in Wireless Sensor Networks

Summary: [This abstract is based on the authors' abstract.] Although they are capable of densely covering a wide area, wireless sensor network sensors have limited sensing, processing, and power capabilities. Information collected by the sensor nodes must be appropriately fused. This study examines the problems of estimating the location of a target and estimating its signal intensity. Proposed algorithms are based on the local vote decision fusion mechanism. While these corrected decisions improve detection, they are correlated, making maximum likelihood estimation intractable. A pseudo-likelihood formulation is adopted, and variants of localization and signal estimation algorithms are examined. Uncertainty assessments of the parameters of interest are provided. Extension to tracking moving targets and localizing multiple targets are also considered.

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  • Topics: Design of Experiments
  • Keywords: Maximum likelihood estimate (MLE), Target, Target value, Decision matrix, Communications techniques, Networks
  • Author: Katenka, Natallia; Levina, Elizaveta; Michailidis, George
  • Journal: Technometrics