Positioning Accuracy Improvement via Distributed Location Estimate in Cooperative Vehicular Networks

TL;DR

This paper presents a decentralized cooperative localization algorithm that enhances vehicular positioning accuracy by utilizing GPS pseudorange measurements and inter-vehicle distances without relying on fixed anchors.

Contribution

It introduces a novel distributed algorithm that improves vehicle localization accuracy using raw GPS data and inter-vehicle measurements, suitable for dynamic vehicular networks.

Findings

Significant improvement in positioning accuracy demonstrated in simulations

Utilizes raw GPS pseudorange measurements instead of traditional radio ranging

Operates without fixed location anchors, enhancing practicality

Abstract

The development of cooperative vehicle safety (CVS) applications, such as collision warnings, turning assistants, and speed advisories, etc., has received great attention in the past few years. Accurate vehicular localization is essential to enable these applications. In this study, motivated by the proliferation of the Global Positioning System (GPS) devices, and the increasing sophistication of wireless communication technologies in vehicular networks, we propose a distributed location estimate algorithm to improve the positioning accuracy via cooperative inter-vehicle distance measurement. In particular, we compute the inter-vehicle distance based on raw GPS pseudorange measurements, instead of depending on traditional radio-based ranging techniques, which usually either suffer from high hardware cost or have inadequate positioning accuracy. In addition, we improve the estimation of the vehicles' locations only based on the inaccurate GPS fixes, without using any anchors with known exact locations. The algorithm is decentralized, which enhances its practicability in highly dynamic vehicular networks. We have developed a simulation model to evaluate the performance of the proposed algorithm, and the results demonstrate that the algorithm can significantly improve the positioning accuracy.