Connectivity Information-Aided Belief Propagation for Cooperative Localization

Abstract

This letter proposes a cooperative localization algorithm based on connectivity information-aided belief propagation that can enhance belief propagation, which relies on the mutual exchange of location information with uncertainty. The connectivity information in the network is used to reduce the location uncertainty in the belief. As a result, it is possible to prevent the message flow of unnecessary location information which makes the location distribution too broad. The proposed algorithm is compared with sum-product algorithm over a wireless network, and shown to provide not only the performance enhancement in the localization accuracy, but also the computational gain when it is implemented by the sampling method.