Performance Evaluation of EGNOS in Challenging Environments

Space-based augmentation systems (SBAS), such as EGNOS, are largely used to complement GPS for accurate and reliable positioning, which is required by rapidly growing location-based services (LBS). However, it is challenging to use EGNOS in the environments including urban areas and marginal area of the monitoring networks, where many LBS are delivered. Through the experiments in the challenging observation conditions, this study first evaluates the performance of EGNOS in these environments. Challenges consist in two aspects: EGNOS signals may be interrupted by blockages; EGNOS messages are not produced at all for marginal geographical areas due to the lack of raw satellite measurements. In order to use EGNOS for enhanced positioning performance in these environments, this paper then discusses several potential solutions. It is concluded that the two autonomous approaches, i.e. using aged corrections and mixing corrected and uncorrected satellites, can improve the positioning accuracy with a stand-alone receiver, and a full EGNOS positioning performance can be achieved in urban areas via a terrestrial access to EGNOS data, for example, the Internet connection with a smartphone. This paper discusses the effectiveness and usability of these approaches.

[1]  Zhang Hongping,et al.  Modeling Regional Ionosphere Using GPS Measurements over China by Spherical Cap Harmonic Analysis Methodology , 2008 .

[2]  Wang Zemin Model of Inter-Frequency Combinations of Galileo GNSS , 2003 .

[3]  Zemin Wang,et al.  GPS based detection of pre-seismic ionospheric abnormality , 2007, Other Conferences.

[4]  Mohinder S. Grewal,et al.  Kalman Filtering: Theory and Practice Using MATLAB , 2001 .

[5]  Richard A. Brown,et al.  Introduction to random signals and applied kalman filtering (3rd ed , 2012 .

[6]  Young Jae Lee,et al.  ARMA model for neural networks predictor of DGPS carrier phase correction , 2007 .

[7]  Ruizhi Chen,et al.  Spherical cap harmonic model for mapping and predicting regional TEC , 2011 .

[8]  Paul Cross,et al.  High Precision GPS IIR Orbit Prediction using Analytical Non-conservative Force Models , 2004 .

[9]  Zhu Wenyao,et al.  Comparison and Consistency Research of Regional Ionospheric TEC Models Based on GPS Measurements , 2008 .

[10]  U Li Approach to MCAR Using Galileo Multi-Carrier Measurements , 2006 .

[11]  Jérôme Leclère,et al.  An Assisted-GNSS Solution for Demanding Road Applications using the EGNOS Data Access System (EDAS) , 2010 .

[12]  Jian Yang,et al.  A Preliminary Study on Mapping the Regional Ionospheric TEC Using a Spherical Cap Harmonic Model in High Latitudes and the Arctic Region , 2010 .

[13]  Dah-Jing Jwo,et al.  ARMA Neural Networks for Predicting DGPS Pseudorange Correction , 2004, Journal of Navigation.

[14]  Bradford W. Parkinson,et al.  Global positioning system : theory and applications , 1996 .

[15]  M. Hernández‐Pajares,et al.  Second-order ionospheric term in GPS : Implementation and impact on geodetic estimates , 2007 .