Sharif Digital Repository

We propose a range-free localization framework in which a network of randomly deployed acoustic sensors can passively use natural acoustic phenomena within its environment to localize itself. We introduce a novel approach for registration of sensors observations which takes advantage of a clustering technique on triplets of associated observations. A Bayesian filtering method is employed to incrementally improve system state estimation as more observations become available. To the best of our knowledge this is the first work done on range-free passive acoustic localization. Simulation experiments of the proposed algorithms are presented. © 2008 IEEE  

Localization of sensor nodes has become a fundamental requirement for many applications over Wireless Sensor Networks (WSNs). In this paper, we propose a range-free approach based on the Received Signal Strength (RSS) changes. A discrete and probabilistic localization method is offered to localize a moving beacon relative to sensor nodes. In this method we came to a more reliable and accurate result without increasing the number of sectors. We achieved a considerable improvement in localization reliability by defining the primary and secondary sectors and utilizing a Kalman approach for making decisions. The decision making process is based on the allocated probabilities given to each of... 

Sensor Localization is a crucial part of many location-dependent applications that is utilized in wireless sensor networks (WSNs). Several approaches, including range-based and range-free, have been proposed to calculate the position of randomly deployed sensor nodes. With specific hardware, the range-based schemes typically achieve high accuracy based on either node-to-node distances or angles. On the other hand, the range-free mechanisms support less positioning accuracy with less expense. The proposed scheme is based on range-free localization, which utilizes the received signal strength (RSS) from the anchor nodes. In this work, genetic fuzzy and neuro-fuzzy methods are used to become...