Decentralized M-ary detection via hierarchical binary decision fusion

Abstract

We consider the distributed M-ary detection problem. The M-ary decision-making process is implemented via a sequence of binary decision-making processes. The resulting binary decisions represent a hierarchical partition of the M-ary object space, which is organized in the form of a binary decision tree. This approach breaks a complex M-ary decision fusion problem into a set of much simpler binary decision fusion problems. We first develop a method for partitioning the M-ary object space. We then obtain the optimal decision rules that the fusion center and the sensors employ at the internal nodes of the binary decision tree. The results are illustrated in an example.