An Enhanced DV-hop Localization Algorithm for Irregularly Shaped Sensor Networks

摘要

Position information in sensor networks is crucial for many applications. A large number of localization algorithms have been developed, however, most of them need special measurement tools and could not work well in irregularly shaped sensor networks. In this paper, we present an Enhanced DV-hop Localization Algorithm (EDLA) to deal with irregularly shaped network topology. With the same process of DV-hop, a reference node of EDLA can delimit approximate regular shaped regions as convex hulls. Based on the inclusion test within convex hulls, the expected average per-hop distance information is disseminated by qualified relay nodes and used for position estimation. Simulation results show that the proposed localization method outperforms DV-hop and PDM(proximity-distance map) in irregularly-shaped sensor networks if both the localization error and computational complexity are considered.