A distributed extended information filter for Self-Localization in Sensor Networks

In this paper the self-localization problem for sensor networks is addressed. Given a set of nodes deployed in an environment, self-localization consists of finding out the location of all nodes in regard to any topology or metric of interest. Nodes are assumed to be equipped with a sensor board able to provide these inter-node distances. In addition, a few nodes are assumed to be equipped with some absolute position devices. According to this scenario, a new distributed algorithm based on an extended information filter is proposed. This algorithm provides an accurate estimation of node positions with a reasonable computational complexity, even when in presence of noisy measurements. Real experiments, carried out by exploiting Micaz Motes platforms, have been performed to show the effectiveness of the proposed technique.