On May 2018 the world’s first dual-frequency Global Navigation Satellite System (GNSS) smartphone produced by Xiaomi equipped with a Broadcom BCM47755 chip was launched. It is able to receive L1/E1/ and L5/E5 signals from GPS, Galileo, Beidou, and GLONASS (GLObal NAvigation Satellite System) satellites. The main aim of this work is to achieve the phone’s position by using multi-constellation, dual frequency pseudorange and carrier phase raw data collected from the smartphone. Furthermore, the availability of dual frequency raw data allows to assess the multipath performance of the device. The smartphone’s performance is compared with that of a geodetic receiver. The experiments were conducted in two different scenarios to test the smartphone under different multipath conditions. Smartphone measurements showed a lower C/N0 and higher multipath compared with those of the geodetic receiver. This produced negative effects on single-point positioning as showed by high root mean square error (RMS). The best positioning accuracy for single point was obtained with the E5 measurements with a DRMS (horizontal root mean square error) of 4.57 m. For E1/L1 frequency, the 2DRMS was 5.36 m. However, the Xiaomi Mi 8, thanks to the absence of the duty cycle, provided carrier phase measurements used for a static single frequency relative positioning with an achieved 2DRMS of 1.02 and 1.95 m in low and high multipath sites, respectively.

An effective approach to reconstruct the normalized radar cross section (NRCS) image from Global Navigation Satellite System-Reflectometry (GNSS-R) Delay-Doppler Map (DDM) is proposed. It is physically based on the truncated singular value decomposition (TSVD), properly extended to the 2-D case (2-D TSVD). The proposed approach is tested against simulated noisy DDMs, where both the additive and multiplicative noise are accounted for. The latter, generally known as speckle, is modeled using a Rice distribution. Experimental results show that the 2-D TSVD can be successfully exploited to reconstruct the NRCS field from DDM noisy measurements. Moreover, an analysis on the spatial resolution which characterizes the reconstructed domain is undertaken: it shows that generally a nonuniform spatial resolution is achieved while an area of the observed scene presents a almost uniform resolution that can be useful for remote sensing purposes

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The Environmental Protection Agency of the Campania region in Italy (ARPAC) manages a groundwater quality monitoring network. For almost all the polluted waters, the key parameter driving the classification is the concentration of nitrate; hence, the Campania region, in coherence with the EU regulations, outlined the vulnerable areas and undertook remediation policies. The best groundwater quality is recorded for carbonate aquifers of the Apennine chain; on the contrary, the Tyrrhenian coastal plains are affected by severe contamination, with a locally very contaminated groundwater of the shallow and also the deeper aquifers. The study is especially focused on a large coastal plain of Campania region, where nitrate concentration sometimes exceeds 200 mg/L. The study, based on almost 200 sampling points for the whole region during the period 2003-2015 (approx two samples per year), verified the effectiveness of the groundwater monitoring network, the present distribution of nitrate in groundwater, and the evolution of nitrate trends at different scales: regional, groundwater body, and single well, using spatial and time series statistical approaches. Significant variations in contamination evolution within the study area have been observed and the correlation with land use has been highlighted.

The integration of Global Navigation Satellite Systems (GNSS) with Inertial Navigation Systems (INS) has been very actively researched for many years due to the complementary nature of the two systems. In particular, during the last few years the integration with micro-electromechanical system (MEMS) inertial measurement units (IMUs) has been investigated. In fact, recent advances in MEMS technology have made possible the development of a new generation of low cost inertial sensors characterized by small size and light weight, which represents an attractive option for mass-market applications such as vehicular and pedestrian navigation. However, whereas there has been much interest in the integration of GPS with a MEMS-based INS, few research studies have been conducted on expanding this application to the revitalized GLONASS system. This paper looks at the benefits of adding GLONASS to existing GPS/INS(MEMS) systems using loose and tight integration strategies. The relative benefits of various constraints are also assessed. Results show that when satellite visibility is poor (approximately 50% solution availability) the benefits of GLONASS are only seen with tight integration algorithms. For more benign environments, a loosely coupled GPS/GLONASS/INS system offers performance comparable to that of a tightly coupled GPS/INS system, but with reduced complexity and development time.