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.
|Original language||English (US)|
|Number of pages||5|
|Journal||IEEE Transactions on Aerospace and Electronic Systems|
|State||Published - Jul 1992|
All Science Journal Classification (ASJC) codes
- Aerospace Engineering
- Electrical and Electronic Engineering