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The location information of sensors is of great importance for wireless sensor network automation and has been one of the major challenges in large-scale sensor networks. In order to improve the localization accuracy of sensors, the gain of both range-free and range-based approaches need to be concerned. In this paper, we propose a new localization algorithm based on signal receiving probability and Procrustes analysis. A critical observation in range-free technique is sensors can move a non-zero distance without changing itâs connectivity information. To defeat that difficulty and achieve a better ranging measurement, a receiving probability function, which is sensitive to the distance, is used in this paper. The probability function is used to calculate the topological coordinates and then to transform it to physical coordinates, the Procrustes analysis is used. The result shows that our proposed algorithm has been able to calculate the physical coordinates of sensors, which are distributed over an area, consist of obstacles and with different environmental conditions. Moreover, it outperformed the other existing algorithms by a maximum localization error less then 2m.

Sensor Localization using Signal Receiving Probability and Procrustes Analysis