GNSS accuracy improvement using rapid shadow transitions

Roi Yozevitch, Boaz Ben-Moshe, Amit Dvir

Research output: Contribution to journalArticlepeer-review

37 Scopus citations

Abstract

Receiver modules in Global Navigation Satellite Systems (GNSS) are capable of providing positioning and velocity estimations that are sufficiently accurate for the purpose of road navigation. However, even in optimal open-sky conditions, GNSS-based positioning carries an average error of 2-4 m. This imposes an effective limitation on GNSS-based vehicle lane detection, a desired functionality for various navigation and safety applications. In this paper, we present a novel framework for lane-level accuracy using GNSS devices and 3-D shadow matching. The suggested framework is based on detection and analysis of rapid changes in navigation satellites' signal strength, which are caused by momentary blockages due to utility and light poles. A method for detecting such momentary changes between line of sight and non line of sight is presented, followed by a geometric algorithm that improves location accuracy of commercial GNSS devices. We have tested the framework's applicability using both simulations and field experiments. We provide the results of these tests and discuss receiver-side sampling rate requirements for high-performance lane-level positioning.

Original languageEnglish
Article number6737254
Pages (from-to)1113-1122
Number of pages10
JournalIEEE Transactions on Intelligent Transportation Systems
Volume15
Issue number3
DOIs
StatePublished - 1 Jan 2014
Externally publishedYes

Keywords

  • Global Navigation Satellite Systems (GNSS) accuracy improvement
  • lane detection
  • shadow matching

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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