Self-localization using nonoutlier triangles in sensor networks

Recent advancements in networking, micro-electromechanical systems technology and computing have made it possible to develop low-cost, low-power, multi-functional sensor nodes. Many potential applications are emerging: environment and habitat monitoring, infrastructure security and industry sensing. Most of these applications require sensor nodes know theirs position information to accomplish their respective tasks and the networking tasks efficiently. Therefore, localization is one of the key issues in sensor networks. In this paper, a novel distributed localization algorithm is proposed utilizing nonoutlier triangles and weighted-centroid for sensor networks. This approach doesn't need a large amount of anchor nodes for achieving high estimation accuracy. Simulations show that this approach can significantly improve localization accuracy and it is robust to range measurement noise and irregular deployment of anchor nodes.