Cooperative Relative Positioning for Intelligent Transportation System

Abstract

Global navigation satellite system-based positioning plays an important role in support system for safe driving, where relative positions of vehicles are used to prevent collision accidents from happening. In urban areas, however, multipath errors (MPEs) in pseudo-ranges, caused by obstruction and reflection of roadside buildings, greatly degrade the precision of relative positions. On the other hand, simply removing all reflected signals might lead to a shortage of satellites in fixing positions. This dilemma is solved in this paper by exploiting spatial correlation of MPEs. First, by analysis, ray-tracing simulation and testbed experiments, we show that MPEs in pseudo-ranges are spatially correlated in a small area. Then, we suggest a cooperative relative positioning scheme to exploit correlated signals, including reflected ones, in computing relative positions of nearby vehicles. Efficient transmission of pseudo-ranges is also discussed. The proposed scheme, which can be implemented either in a distributed way or via a cloud of intelligent transportation system, helps to improve the precision of relative positions in urban canyons.