Networking In Distributed Decision Fusion

Abstract

The networking problem in distributed fusion system is considered. At a given time instant, the decisions from some sensors may not be available at the fusion center due to the transmission delays. Assuming that the fusion center has to make a decision based on the data from the rest of the sensors, provided that at least one peripheral decision has been received, it is shown that the optimal decision rule that minimizes the probability of detection for fixed probability of false alarm at the fusion center is the Neyman-Pearson test at the fusion center and the sensors as well. Whenever the Lagrange multipliers method holds valid, the optimal set of thresholds is given via a set of nonlinear, coupled equations that depend on the decision policy and cannot be solved in general. A suboptimal, computational efficient algorithm is developed to solve for the sensor and fusion thresholds sequentially. Numerical results are provided to demonstrate the closeness of the solutions obtained by the suboptimal algorithm to the optimal solutions.