PROJECT TITLE :

Distributed Event Localization via Alternating Direction Method of jMultipliers - 2018

ABSTRACT:

This Project addresses the problem of distributed event localization using noisy vary measurements with respect to sensors with known positions. Event localization is key in several wireless sensor network applications like homeland security, law enforcement, and environmental studies. However, most existing distributed algorithms need the target event to be inside the convex hull of the deployed sensors. Based mostly on the alternating direction methodology of multipliers (ADMM), we tend to propose 2 scalable distributed algorithms named GS-ADMM and J-ADMM which do not require the target event to be within the convex hull of the deployed sensors. A lot of specifically, the 2 algorithms will be implemented in a very situation in which the entire sensor network is divided into several clusters with cluster heads collecting measurements at intervals every cluster and exchanging intermediate computation data to attain localization consistency (consensus) across all clusters. This state of affairs is very important in many applications such as homeland security and law enforcement. Simulation results confirm effectiveness of the proposed algorithms.