Analysis of hybrid and cooperative positioning algorithms in urban canyon scenarios

Abstract

Dense urban areas are particularly challenging environments for global navigation satellite systems (GNSS) because the satellite visibility is heavily reduced due to the presence of the so called urban canyons, composed of a series of tall buildings and narrow streets. In order to improve GNSS performance in these environments, hybrid (GNSS/terrestrial) and cooperative positioning algorithms that combine pseudorange measurements from visible satellites and terrestrial range measurements from neighboring terrestrial receivers have been recently proposed in the literature. Mainly, these algorithms have been tested in static or pedestrian mobility scenarios. This paper, first introduces a robust procedure that selects the most reliable neighbors for cooperation and then analyzes the performance of the optimized hybrid and cooperative positioning algorithms in a typical urban canyon scenario for vehicular navigations. Simulation results demonstrate that the positioning algorithms can accurately track the movement of vehicles in urban canyons even without fixed terrestrial infrastructure. Moreover, an accurate complexity analysis of the different hybrid algorithms is presented to understand their suitability for a real implementation.