A hypothesis testing method for multisensory data fusion

Presents a hypothesis testing method called double bound testing which is used for statistical decision-making, specifically for binary decisions. A probability decision space is defined to increase the decision flexibility. Based on the decision reached by each sensor, a combination rule is also formulated to give the global decision for the multisensor system. The proposed method offers three options for decision snaking, rather than the classical binary options. An experiment on 2D object identification was performed to demonstrate the proposed strategy