Weighted Centroid Localization algorithm based on least square for wireless sensor networks

Localization algorithm is an important and challenging topic in today's wireless sensor networks (WSNs). In order to improve the localization accuracy, a weighted centroid localization algorithm based on least square to predict the location of any sensor in a WSNs is proposed in this paper. The proposed algorithm proposes a Least-Square-based weight model which can reasonably weigh the proportion of each anchor node in the unknown node. In the weight model, we utilize least square method to compute the weight. Then, we increase the weight of anchor nodes closer to the unknown node, introduce the parameter k into the proposed likelihood model, and we determine the optimal value of the parameter k through our experiments. Experimental results show that the proposed weighted centroid algorithm is better than WCL (Weighted Centroid Localization) and AMWCL-RSSI (anchor-optimized modified weighted centroid localization based on RSSI) in terms of the localization accuracy.