Table of Contents
International Journal of Navigation and Observation
Volume 2012, Article ID 132078, 10 pages
http://dx.doi.org/10.1155/2012/132078
Research Article

On the Impact of Channel Cross-Correlations in High-Sensitivity Receivers for Galileo E1 OS and GPS L1C Signals

1Istituto Superiore Mario Boella, Via P.C. Boggio 61, 10138 Torino, Italy
2Department of Electronics and Telecommunications, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy

Received 31 December 2011; Accepted 5 April 2012

Academic Editor: Shaojun Feng

Copyright © 2012 Davide Margaria et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

One of the most promising features of the modernized global navigation satellite systems signals is the presence of pilot channels that, being data-transition free, allow for increasing the coherent integration time of the receivers. Generally speaking, the increased integration time allows to better average the thermal noise component, thus improving the postcorrelation SNR of the receiver in the acquisition phase. On the other hand, for a standalone receiver which is not aided or assisted, the acquisition architecture requires that only the pilot channel is processed, at least during the first steps of the procedure. The aim of this paper is to present a detailed investigation on the impact of the code cross-correlation properties in the reception of Galileo E1 Open Service and GPS L1C civil signals. Analytical and simulation results demonstrate that the S-curve of the code synchronization loop can be affected by a bias around the lock point. This effect depends on the code cross-correlation properties and on the receiver setup. Furthermore, in these cases, the sensitivity of the receiver to other error sources might increase, and the paper shows how in presence of an interfering signal the pseudorange bias can be magnified and lead to relevant performance degradation.