DISTRIBUTED DETECTION WITH MULTIPLE SENSORS .1. FUNDAMENTALS

In this paper, basic results on distributed detection are reviewed. In particular, we consider the parallel and the serial architectures in some detail and discuss the decision rules obtained from their optimiz ation based on the Neyman-Pearson (NP) criterion and the Bayes formula tion. For conditionally independent sensor observations, the optimalit y of the likelihood ratio test (LRT) at the sensors is established. Ge neral comments on several important issues are made including the comp utational complexity of obtaining the optimal solutions, the design of detection networks with more general topologies, and applications to different areas.