Obstacle-resistant hybrid localisation algorithm

A wide range of wireless sensor applications need to know the position of the nodes in a network area. So, finding the location of nodes, which is known as the localisation, has become a challenge in wireless sensor networks. This study proposed Diagonal-Centroid and Diagonal-Particle Swarm Optimisation (PSO) methods, which are regarded as two novel anchor-based localisation techniques. In these methods, the anchor node diagonally traversed the network area and transmit broadcast packets of its position. In Diagonal-Centroid method, nodes estimated their location by the average of the received position while, in the second method, the best tree positions were selected by a heuristic algorithm to estimate the position of the nodes. In this study, the authors extend their analysis to three different scenarios including the networks with and without obstacles to investigate the effect of the obstacles in network localisation, as well as the network with different node deployments to check out the localisation coverage area and network performance. All scenarios were implemented in OMNeT++ simulator, and based on the results, the Diagonal-Centroid technique had the best accuracy, whereas Diagonal-PSO had better performance regarding the accuracy and energy consumption compared to those reported in the other related studies.