While the use of the Global Positioning System provides a natural choice for sensor network localization, the high-accuracy requirements of certain applications prevent the use of low-cost GPS hardware as part of their localization solution. Low cost GPS hardware provides poor accuracy when used in isolation, but the sharing of measurement data between a network of common GPS receivers provides an opportunity to mitigate errors and provide a sub-meter localization solution. The goal of this work is to develop such a system by creating robust techniques that are resilient to outliers and other error sources encountered in the real-world.

For outdoor navigation, GPS provides the most widely-used means of node localization; however, the level of accuracy provided by low-cost receivers is typically insufficient for use in high-precision applications. Additionally, many of these applications do not require precise absolute Earth coordinates, but rather rely on relative positioning to infer information about the geometric configuration of the constituent nodes in a system. This paper presents a novel approach that uses GPS to derive relative location information for a scalable network of single-frequency receivers. Networked nodes share their raw satellite observations, enabling each node to localize its neighbors in a pairwise fashion as opposed to computing its own standalone position. Random and systematic errors are mitigated in novel ways, challenging long-standing beliefs that precision GPS systems require extensive stationary calibration times or complex equipment configurations. In addition to presenting the mathematical basis for our technique, a working prototype is developed, enabling experimental evaluation of several real-world test scenarios. The results of these experiments indicate sub-meter relative positioning accuracy under various conditions and in varying environments. This represents up to order of magnitude increase in precision over existing absolute positioning techniques or other unimodal GPS-based solutions.

One of the primary limitations to widescale adoption of many of today's high-precision location-aware applications is the cost associated with achieving the levels of accuracy necessary for safe and reliable operation. We have developed a relative localization solution enabling centimeter-scale positioning of a network of mobile nodes. The success of this research in the relative sense can be coupled with the known locations of a set of stationary nodes as well as the computational power of the cloud to open the door for an absolute localization service, whereby base stations at well-known locations can be used to transform relative coordinates into absolute locations. We will demonstrate the current progress of our work via live walking and driving experiments in which observers in an exhibition hall can issue commands to walkers and drivers in the field and see the results of these commands as determined by our positioning system in real-time.