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Ionospheric scintillation causes rapid fluctuations of measurements from Global Navigation Satellite Systems (GNSSs), thus threatening space-based communication and geolocation services. The phenomenon is most intense in equatorial regions, around the equinoxes and in maximum solar cycle conditions. Currently, ionospheric scintillation monitoring receivers (ISMRs) measure scintillation with high-pass filter algorithms involving high sampling rates, e.g. 50 Hz, and highly stable clocks, e.g. an ultra-low-noise Oven-Controlled Crystal Oscillator. The present paper evolves phase scintillation indices implemented in conventional geodetic receivers with sampling rates of 1 Hz and rapidly fluctuating clocks. The method is capable to mitigate ISMR artefacts that contaminate the readings of the state-of-the-art phase scintillation index. Our results agree in more than 99.9% within ± 0.05 rad (2 mm) of the ISMRs, with a data set of 8 days which include periods of moderate and strong scintillation. The discrepancies are clearly identified, being associated with data gaps and to cycle-slips in the carrier-phase tracking of ISMR that occur simultaneously with ionospheric scintillation. The technique opens the door to use huge databases available from the International GNSS Service and other centres for scintillation studies. This involves GNSS measurements from hundreds of worldwide-distributed geodetic receivers over more than one Solar Cycle. This overcomes the current limitations of scintillation studies using ISMRs, as only a few tens of ISMRs are available and their data are provided just for short periods of time.

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The hazardous effects of spoofing attacks on the global navigation satellite system (GNSS) receiver are well known. Technologies and algorithms to increase the awareness of GNSS receivers against such attacks become more important and necessary. We present the validation of two statistical spoofing detection methods, namely the Chisquare goodness of fit (GoF) test and the Sign test applied to pairwise correlator differences, for each satellite tracked by the receiver. The test bench for the algorithms, both implemented in a software receiver, is the public database produced by the University of Texas at Austin, which reproduces various representative cases of spoofing attacks (the so-called TEXBAT). The algorithms show a very promising capability of detecting the attack, in particular when an aggregate decision is taken based on a joint detection upon all the tracked satellites. Furthermore, the GoF test appears also reliable in dynamic conditions and in case of a huge power advantage of the spoofing signal. The response of the receiver to the attacks confirms the spoofing signal represents an ''extraneous agent'' which, before taking control of the receiver, can be recognized by properly combined strategies of signal quality monitoring.

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