Self-Organized, Scalable GPS-Free Localization of Wireless Sensors

Wireless sensors are expected to be widely deployed in the near future for a vast variety of applications. Sensing data is not useful unless the location where the data is collected is also known to the end users. Although much work has been done on the positioning of sensor nodes, proposed algorithms often are not applicable in certain environments. Furthermore, there is always a need to reduce their complexity and cost, and to improve accuracy for these algorithms. This work is primarily motivated by a new research project called WINES to deploy wireless sensors to monitor the conditions of London underground and water systems. Global Positioning System (GPS) based positioning methods are not applicable in the underground environments. In addition, the tunnels and water pipes are not located at the same horizontal level, so existing algorithms proposed for two-dimensional deployment areas become inadequate. To overcome the challenge, we propose and study here a new localization algorithm by extending one proposed for two-dimensional service areas by Capkun et al. Our new scheme is a distributed, self-organized, infrastructure-free positioning algorithm that enables easy and flexible sensor deployment in the harsh environments. Furthermore, our computer simulation reveals that the new scheme achieves a satisfactory, relative average position error of less than 5% when the errors for distance estimations among sensors have a standard deviation of no more than 5%.