Ionospheric scintillation effects on GNSS: monitoring and data treatment development

The increasing importance of satellite navigation technologies in modern society implies that a deeper knowledge and a reliable monitoring of the scintillation phenomena are essential to warn and forecast information to the end users and system designers. In fact, warnings, alerts and forecasting of ionospheric conditions may wisely tune the development of GNSS-based services to obtain the necessary levels of accuracy, integrity, and immediacy for reliable life-critical applications. The PhD research project is within the framework of the longstanding NGI-INGV collaboration, increasingly consolidated in the framework of many international projects. NGI pioneered GPS ionospheric scintillation monitoring in Northern Europe with GISTM (GPS ionospheric scintillation and TEC monitor, Van Dierendonck et al., 1993; Van Dierendonck, 2001) receivers. Between June 2001 and December 2003, four units were installed in the UK and Norway mainland, covering the geographic latitudes from 53° N to 70° N. Data was stored and analysed, focusing on statistical analyses and impact for GNSS users (Rodrigues et al., 2004, Aquino et al., 2005a, Aquino et al., 2005b). These units were decommissioned in 2004 and, then, re-deployed together with additional new receivers, in UK, Norway, Italy and Cyprus. An additional station was deployed by the NGI in Dourbes, Belgium (in collaboration with the Royal Meteorological Institute of Belgium) between 2006 and 2011. INGV leads the ISACCO (Ionospheric Scintillation Arctic Campaign Coordinated Observations) project in the Arctic, started in 2003, in which frame the management of three GISTM receivers in Svalbard (De Franceschi et al., 2006) and another two at European mid-latitudes, Chania (Greece) and Lampedusa (Italy), is currently undertaken. The PhD research project contributed to the reinforcement of the NGI-INGV GISTM network developing monitoring, data management and quality tools. Such activities have supported the continuity and the control of the receiving stations, as well as the access and the preservation of the both real-time and historical data acquired. In fact, a robust, continuous data acquisition and a wise management of the GISTM network are of paramount importance for Space Weather applications, as they are the basis on which reliable forecasting and now-casting of possible effects on technological systems lean. Moreover, the possibility to use the data for scientific and applicative purposes depends upon well-established data quality procedures and upon a detailed knowledge of the sites in which each receiver comprising the network are deployed. Starting from these considerations, and in the framework of the aforementioned collaborative context, the PhD work aimed at improving the monitoring techniques and developing novel data processing to improve the data quality. Scintillation measurements are contaminated by multiple scattering encountered by the GNSS signal due to buildings, trees, etc. Such multipath sources need to be identified to keep the quality of the scintillation and TEC data as higher as possible. This can be achieved by removing these sources of errors or mitigating their effects by filtering the data. A novel station characterization technique has been introduced, developed and discussed in this thesis. The results demonstrated that this is a promising method to improve the quality of data (Romano et. al 2013). The results obtained so far motivated the development of the data filtering procedures. The filtering was aimed at filtering-out spurious, noisy data based on general assumptions about statistical data analysis (outlier analysis), thus efficiently removing multipath affected measurements and reducing the data loss with respect to applying a fixed elevation angle cut-off threshold. This is particularly important in case of not well covered regions (e.g. forests, deserts, oceans, etc.), as the field of view spanned by each antenna is optimized. During the PhD activities, the filtering technique has been also tested and validated against real and simulated data. To show how the development of the filtering method is able to efficiently clean multipath and signal degradation from GNSS data, it was applied in two different cases: - First, it was applied to the data published in a climatological study (Alfonsi et al. 2011), carried out with the NGI-INGV GISTM network at high-latitudes. Each station was characterized using the station characterization method, and then the data were filtered using the filtering method. Then, the new climatological maps were generated and compared to the original ones. The percentage of the filtered-out data obtained by applying the standard threshold of 20° on the elevation angle and the filtering technique for each station demonstrated how the latter is able to meaningfully reduce the data loss. The filtering extends the field of view of the network and, then, improves the capability of investigating the dynamics of the ionosphere over larger areas. - Second, the data used in this application were acquired by the CIGALA/CALIBRA network of PolaRxS receivers during the whole year of 2012. The elevation angle cut-off significantly reduced the capability of the network to depict the ionosphere northward of the geomagnetic equator and above the Atlantic Ocean, east of Brazil. This approach limited the data loss to 10-20%, while the traditional cut off of 15°-30° on the elevation angle led to losses of 35-45%. This method not only optimized the capability of GNSS networks, but also helped in planning the installation of additional new receivers aiming to enlarge network coverage in the framework of the CALIBRA project. The enlarged field of view made it possible to identify the increased occurrence of scintillation along the northern crest of the Equatorial Ionospheric Anomaly (EIA). To summarize and to introduce the reader into this thesis, specific issues here addressed are: - Development of software procedures and hardware designs to optimize the station configurations of the existing measurement network of GISTM (GPS Ionospheric Scintillation and TEC Monitor). - Development of techniques for remote, automatic instrument control and setting. - Development of data management tools to achieve quasi real-time data accessibility. - Development of data analysis methods to assess station characterization. - Development of techniques to perform data quality filtering. - Perform acquisition of experimental and simulation data. - Support scientific investigations through the high quality of the NGI-INGV network data