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Global Navigation Satellite Systems: An Enabler for In-Vehicle Navigation

  • John-Olof Nilsson
  • Dave Zachariah
  • Isaac Skog
Reference work entry

Abstract

The emergence of global navigation satellite systems (GNSSs) has enabled tremendous development in vehicular navigation for various applications. The GNSS technology provides a unique global positioning capability with meter-level accuracy at a low hardware cost and zero marginal infrastructure cost. The GNSSs work by using the satellites as radio beacons, broadcasting a satellite-specific signal and their own position. The range to the satellites is measured up to a common clock offset, and any user equipped with a GNSS receiver capable of receiving the signal from four or more satellites can position itself by multilateration. The position, being a fundamental piece of information for automatizing and facilitating location-dependent system interaction and services, makes the GNSS an enabling technology for many intelligent vehicle and transportation system capabilities.

This chapter will focus on introducing the basic principles of the GNSS technology and the signal processing that allows the GNSS receiver to determine its position: in Sect. 1, the technology, its limitations, and currently available GNSSs are reviewed; in Sect. 2, the principles of the GNSS positioning, the signal characteristics, and fundamental components are discussed; in Sect. 3, the theoretical relations governing the positioning are presented; in Sect. 4, implementation-related issues, error sources, and GNSS receivers are discussed; in Sect. 5, the method of differential GNSS is introduced and current augmentation systems are reviewed; and finally in Sect. 6, conclusions are drawn and references, for further reading about different aspects of the GNSS technology, are given.

Keywords

Global Position System Global Navigation Satellite System Global Navigation Satellite System Carrier Phase Augmentation System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London Ltd. 2012

Authors and Affiliations

  1. 1.School of Electrical EngineeringKTH Royal Institute of TechnologyStockholmSweden

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