Abstract:
In this paper, we consider a binary distributed detection system in which a system of
multiple sensors monitors a common volume and provides relevant binary decisions
about the state of the environment to a data fusion center. The fusion center combines
the binary decisions of the individual distributed sensors into a final global decision. We
propose a new hard decision integration method for multiple sensor decision fusion
systems. The proposed hard decision fusion method determines the false alarm
probabilities and the detection probabilities that yield maximum performance. The
performance of the proposed method is provided in case of Rayleigh distributed
observations and is proved to be simple and efficient.