Global optimization for distributed and quantized Bayesian detection system

Global optimization of distributed detection system with multi-bit sensor output requires simultaneous solution of optimum fusion rule and of optimum quantizer mappings for individual sensors. For fixed sensor quantizer mappings, the optimal fusion rule can be easily shown to be a likelihood ratio test. But for a fixed fusion rule, the optimal quantizer mappings are very difficult to determine. In this paper, we consider the case of conditionally independent sensors. The optimal quantizer mappings for fixed fusion rule are derived, and optimal solution to the global optimization problem is obtained through a numerical algorithm.