3D node localization from node-to-node distance information using cross-entropy method

Abstract

This paper proposes a 3D node localization method that uses cross-entropy method for the 3D modeling system. The proposed localization method statistically estimates the most probable positions overcoming measurement errors through iterative sample generation and evaluation. The generated samples are evaluated in parallel, and then a significant speedup can be obtained. We also demonstrate that the iterative sample generation and evaluation performed in parallel are highly compatible with interactive node movement.