Decision Fusion from Heterogeneous Sensors in Surveillance Sensor Systems

Using multiple, heterogeneous sensors in surveillance systems is desirable, not only to tolerate sensor failures, but also to increase the accuracy of the event detection process and to provide complementary capability under different operating conditions. In the operation of multiple, heterogeneous sensors, we may encounter inconsistent sensor observations. Motivated by the need to make coherent decisions, we propose in this study a decision scheme to determine the right interpretations of sensor outputs when conflict arises. The proposed decision rule considers sensor heterogeneity in a surveillance system, while attempting to minimize the expected misclassification cost. Case studies of the surveillance sensor system in a major U.S. port demonstrate that the proposed decision scheme achieves a better robustness in the presence of sensor failures than the popular k -out-of-n decision fusion rule.