Object tracking and monitoring is currently extensively implemented by distributed wireless sensor networks whose architectures, operations, and performance demands are dictated by the tracking and monitoring objectives, but are also constrained by the characteristics and limitations of the environment. Within the statistical inference domain, the tracking and monitoring objectives are classified as either hypothesis testing (detection) or parameter estimation or estimation of the acting data generating process, and the pertinent performance criteria include decision/estimation accuracy and convergence rate, where detection/estimation accuracy is generally monotonically increasing with the number of observation data processed. When time constraints are imposed on high accuracy detection/estimation, the consequence is increased required overall data rates.

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