IEEE Transactions on Aerospace and Electronic Systems · 1989 · 206 citations · 15 references
ComputingDecision SciencesMathematicsDecision TheoryDistributed SystemsProbability TheoryBayesian Decision TheoryDecision-level FusionDistributed SensingDistributed Sensor NetworksSensor NetworksSignal Detection TheoryDistributed FusionDistributed Sensor FusionFalse Alarm AnalysisFusion Decision MakingLikelihood Ratio TestingLikelihood Ratio TestsOptimal Decision MakingOptimal Decision Theory
The problem of decision fusion in distributed sensor systems is considered. Distributed sensors pass their decisions about the same hypothesis to a fusion center that combines them into a final decision. Assuming that the sensor decisions are independent of each other for each hypothesis, the authors provide a general proof that the optimal decision scheme that maximizes the probability of detection at the fusion for fixed false alarm probability consists of a Neyman-Pearson test (or a randomized N-P test) at the fusion and likelihood-ratio tests at the sensors.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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