Abstract
The problem of decision fusion in distributed sensor system is considered. Distributed sensors pass their decisions about the same hypotheses to a fusion center that combines them into a final decision. Assuming that the semor decisions are independent from each other conditioned on each hypothesis, we provide a general proof that the optimal decision scheme that maximizes the probability of detection at the fusion for fixed false alarm probability comists of a Neyman-Pearson test (or a randomized N-P test) at the fusion and likelihood-ratio tests at the sensors.
Recommended Citation
Thomopoulos, S. C., Viswanathan, R. and Bougoulias, D. K. "Optimal Distributed Decision Fusion." (Sep 1989).
COinS
Comments
Published Thomopoulos, S.C.A., Viswanathan, R., & Bougoulias, D.K. (1989). Optimal distributed decision fusion. IEEE Transactions on Aerospace and Electronic Systems, 25(5), 761-765. doi: 10.1109/7.42092 ©1989 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.