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Sensor Information Processing

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Sensor information processing constitutes an important component of sensor networks both at the fundamental research level as well as at its usefulness to various applications. There are fsix research areas in signal processing that include: wireless time-synchronized COTS sensor platform for beamforming; the theory and implementation of coherent acoustic array processing and localization on distributed sensor network; entropy-based sensor selection for localization; fundamental information theoretic limits in large-scale sensor networks; cooperative communications; and adaptive communication in sensor array for biologically motivated systems. Basic as well as applied research and theoretical as well as system results are reported below. There are definite synergistic benefits derived from interactions among these six areas and across the theoretical and applied research efforts.


Our original research objectives for the first two years were to: identify basic concepts on sensor placements for efficient sensor data collection, processing, and transmission relevant to the NSF Center; identify applications of array processing and data management techniques to the four proposed experiments with particular emphasis on habitat sensing array and spatially dense seismic sensing. In addition, fundamental issues in the information theory of sensor networks and cooperative communications were to be investigated to determine broad design principles across applications. Another direction of our research is the study of adaptive communication in sensor arrays motivated by biological systems.

In the current reporting period, our research activities are consistent with the original proposed objectives as can be seen with the five main research accomplishments described in some detail in section 5.