LaMSM: Localization Algorithm with Merging Segmented Maps for Underwater Sensor Networks

Underwater sensor networks (UWSNs) are considered a costeffective solution to ocean applications, such as the acquisition of natural resources in oceans, protection from underwater disasters, etc. These applications basically require location information of nodes to identify the venue of reported events. To locate more accurately the position of nodes, multidimensional scaling (MDS) is widely used because of its good tolerance to errors in measured distances. MDS requires measured distances between every pair of nodes but in practice, only distances between nodes within a communication range can be measured. Hence, the well-known MDS-MAP(P) [6] calculates unmeasured distances for MDS but these calculations result in large errors. In this paper, we proposed a localization algorithm with merging segmented maps (LaMSM) that constructs many reliable segmented maps composed of only nodes within a communication range, and then merges them together based on their common nodes. The segmented maps are built from only the measured distances and as a result, LaMSM provides more accurate node positions than MDS-MAP(P).