A novel distance estimation approach for 3D localization in wireless sensor network using multi dimensional scaling

Node localization is very important in Wireless Sensor Network (WSN) and distance estimation between pairs of nodes is the prerequisite for localization and thus the applicability of the reported events. The paper proposes a novel distance estimation algorithm to estimate distances of each node to every other node in the network. The main contribution of the paper is the definition of a dissimilarity matrix representing the distance of each node to every other node in the network. MDS based localization algorithm is used to determine coordinates of the node in a local coordinate system and Helmert Transformation is used to convert the local coordinates of the node into a global coordinate system. The effect of various parameters affecting the performance of proposed algorithm is also presented in the paper. Finally, the efficiency of the proposed algorithm is established through the simulation results.