Abstract

This work reviews an ionospheric activity indicator useful for identifying disturbed periods affecting the performance of Global Navigation Satellite System (GNSS). This index is based in the Along Arc TEC Rate (AATR) and can be easily computed from dual-frequency GNSS measurements. The AATR indicator has been assessed over more than one Solar Cycle (2002–2017) involving about 140 receivers distributed world-wide. Results show that it is well correlated with the ionospheric activity and, unlike other global indicators linked to the geomagnetic activity (i.e. DST or Ap), it is sensitive to the regional behaviour of the ionosphere and identifies specific effects on GNSS users. Moreover, from a devoted analysis of different Satellite Based Augmentation System (SBAS) performances in different ionospheric conditions, it follows that the AATR indicator is a very suitable mean to reveal whether SBAS service availability anomalies are linked to the ionosphere. On this account, the AATR indicator has been selected as the metric to characterise the ionosphere operational conditions in the frame of the European Space Agency activities on the European Geostationary Navigation Overlay System (EGNOS). The AATR index has been adopted as a standard tool by the International Civil Aviation Organization (ICAO) for joint ionospheric studies in SBAS. In this work we explain how the AATR is computed, paying special attention to the cycle-slip detection, which is one of the key issues in the AATR computation, not fully addressed in other indicators such as the Rate Of change of the TEC Index (ROTI). After this explanation we present some of the main conclusions about the ionospheric activity that can extracted from the AATR values during the above mentioned long-term study. These conclusions are: (a) the different spatial correlation related with the MOdified DIP (MODIP) which allows to clearly separate high, mid and low latitude regions, (b) the large spatial correlation in mid latitude regions which allows to define a planetary index, similar to the geomagnetic ones, (c) the seasonal dependency which is related with the longitude and (d) the variation of the AATR value at different time scales (hourly, daily, seasonal, among others) which confirms most of the well-known time dependences of the ionospheric events, and finally, (e) the relationship with the space weather events.

Highlights

  • The Earth ionosphere is defined as the upper part of the atmosphere where ions and free electrons are present in quantities sufficient to affect the propagation of radio waves (IEEE, 1997)

  • The Along Arc Total Electron Content (TEC) Rate (AATR) indicator has been assessed over more than one Solar Cycle (2002–2017) involving about 140 receivers distributed world-wide. Results show that it is well correlated with the ionospheric activity and, unlike other global indicators linked to the geomagnetic activity (i.e. Disturbance Storm Time (DST) or Ap), it is sensitive to the regional behaviour of the ionosphere and identifies specific effects on Global Navigation Satellite System (GNSS) users

  • In this work we explain how the AATR is computed, paying special attention to the cycle-slip detection, which is one of the key issues in the AATR computation, not fully addressed in other indicators such as the Rate Of change of the TEC Index (ROTI). After this explanation we present some of the main conclusions about the ionospheric activity that can extracted from the AATR values during the above mentioned long-term study

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Summary

Introduction

The Earth ionosphere is defined as the upper part of the atmosphere where ions and free electrons are present in quantities sufficient to affect the propagation of radio waves (IEEE, 1997). Global indices linked to the Sun (e.g., the Sun Spot Number (SSN) or the F10.7 centimetre Solar radio flux) are well suited to describe the total ionization level of the ionosphere (Hathaway, 2010); or linked to the Earth magnetic field (e.g., Kp, Ap, DST) which is perturbed by changes in the Solar wind (Rostoker, 1972).

The AATR index
Data preprocessing: cycle-slip detection
Computation of the AATR
Experimental data
Temporal dependency
Latitude dependency
Longitude dependency
10 Post-sunset Events
Space weather
Correlation of AATR
Index proposal
N AATR
Application of the AATR to navigation
Conclusions
Full Text
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