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Distributed-sensor-system decision analysis using team strategies

A distributed (or decentralized) multiple sensor system is considered under binary hypothesis environments. The system is deployed with a host sensor (HS) and multiple slave sensors (SSs). All sensors have their own independent decision makers which are capable of declaring local decisions based solely on their own observation of the environment. The communication between the HS and the SSs is conditional upon the HS's command. Each communication that takes place involves a communication cost which plays an important role in the approaches taken in this study. The conditional communication with the cost initiates the team strategy in making the final decisions at the HS. The objectives are not only to apply the team strategy method in the decision making process, but also to minimize the expected system cost (or the probability of error in making decisions) by optimizing thresholds in the HS> The analytical expression of the expected system cost (C) is numerically evaluated for Gaussian statistics over threshold locations in the HS to find an optimal threshold location for a given communication cost. The computer simulations of various sensor systems for Gaussian observations are also performed in order to understand the behavior of each system with respect to correct detections, false, alarms, and target misses.