Optimal Data Fusion of Correlated Local Decisions in Multiple Sensor Detection Systems

Abstract

Recently, Chair and Varshney have solved the data fusion problem for fixed binary local detectors with statistically independent decisions. We generalize their solution by using the Bahadur-Lazarsfeld expansion of probability density functions. The optimal data fusion rule is developed for correlated local binary decisions, in terns of the conditional correlation coefficients of all orders. We show that when all these coefficients are zero, the rule coincides with the original Chair-Varshney design. © 1992 IEEE