Title :
Optimal data fusion of correlated local decisions in multiple sensor detection systems
Author :
Kam, Moshe ; Zhu, Qingdong ; Gray, W. Steven
Author_Institution :
Dept. of Electr. & Comput. Eng., Drexel Univ., Philadelphia, PA
fDate :
7/1/1992 12:00:00 AM
Abstract :
Z. Chair and P.R. Varshney (1986) solved the data fusion problem for fixed binary local detectors with statistically independent decisions. Their solution is generalized by using the Bahadur-Lazarsfeld expansion of probability density functions. The optimal data fusion rule is developed for correlation local binary decisions, in terms of the conditional correlation coefficients of all orders. It is shown that when all these coefficients are zero, the rule coincides with the original Chair-Varshney design
Keywords :
correlation methods; decision theory; probability; signal detection; signal processing; Bahadur-Lazarsfeld expansion; Chair-Varshney design; binary decisions; conditional correlation coefficients; correlated local decisions; data fusion; fixed binary local detectors; multiple sensor detection; probability density functions; Application software; Bayesian methods; Costs; Detectors; Digital-to-frequency converters; Laboratories; Mathematics; Probability density function; Sensor fusion; Sensor systems;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
