Copula-based fusion of correlated decisions
- Syracuse University
- ORNL
Detection of random signals under a distributed setting is considered. Due to the random nature of the spatial phenomenon being observed, the sensor decisions collected at the fusion center are correlated. Assuming that local detectors are single threshold binary quantizers, a novel approach for the fusion of correlated decisions is proposed using the theory of copulas. The proposed approach assumes only the knowledge of the marginal distribution of sensor observations but no prior knowledge of their joint distribution. Using a Neyman-Pearson (NP) framework for detection at the fusion center, the optimal fusion rule is derived. An example involving the detection of nuclear radiation is presented to illustrate the proposed approach, and results demonstrating the efficiency of the copula-based fusion rule are shown.
- Research Organization:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC05-00OR22725
- OSTI ID:
- 1649671
- Journal Information:
- IEEE Transactions on Aerospace & Electronics Systems, Journal Name: IEEE Transactions on Aerospace & Electronics Systems Journal Issue: 1 Vol. 47
- Country of Publication:
- United States
- Language:
- English
Similar Records
Distributed detection with multiple sensors: Part I - fundamentals
On the quantification and efficient propagation of imprecise probabilities with copula dependence