L'abstract è  presente nell'allegato / the abstract is in the attachmen

IMAM, RAYAN MOHAMED ELMUBARAK ALI

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L'abstract è  presente nell'allegato / the abstract is in the attachmen

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21 December 2022POLITECNICO DI TORINORepository ISTITUZIONALEGlobal Navigation Satellite Systems as Signals of Opportunity for Environmental Applications: Reflectometry andScintillation / Imam, RAYAN MOHAMED ELMUBARAK ALI. - (2022 Dec 01), pp. 1-199.OriginalGlobal Navigation Satellite Systems as Signals of Opportunity for Environmental Applications:Reflectometry and ScintillationPublisher:PublishedDOI:Terms of use:openAccessPublisher copyright(Article begins on next page)This article is made available under terms and conditions as specified in the  corresponding bibliographic description inthe repositoryAvailability:This version is available at: 11583/2973801 since: 2022-12-13T12:25:13ZPolitecnico di TorinoDoctoral DissertationDoctoral Program in Electrical, Electronics and Communications Engineering(34thcycle)Global Navigation Satellite Systemsas Signals of Opportunityfor Environmental ApplicationsReflectometry and ScintillationByRayan Imam******Supervisor(s):Prof. Fabio Dovis, SupervisorDoctoral Examination Committee:Prof. A.B. , Referee, University of...Prof. C.D, Referee, University of...Prof. E.F, University of...Prof. G.H, University of...Prof. I.J, University of...Politecnico di Torino2022DeclarationI hereby declare that, the contents and organization of this dissertation constitute myown original work and does not compromise in any way the rights of third parties,including those relating to the security of personal data.Rayan Imam2022* This dissertation is presented in partial fulfillment of the requirements for Ph.D.degree in the Graduate School of Politecnico di Torino (ScuDo).Global Navigation Satellite Systemsas Signals of Opportunityfor Environmental ApplicationsRayan ImamThe proposals on opportunistically utilizing Global Navigation Satellite Systems’(GNSS) signals for environmental monitoring came to light hand in hand withproposing the GNSS systems themselves. GNSS satellites broadcast signals that canbe exploited for positioning, navigation and timing anywhere and at any time on Earth.The high temporal and geographic availability of the GNSS satellites, together withparticular properties of the GNSS signals, made them an ideal remote sensing tool.Here, the satellites are considered as radio signals sources to be utilized by passiveremote sensing sensors. Many applications have been successfully deployed basedon this concept including GNSS-Reflectometry (GNSS-R), and GNSS scintillation.Today, less than 50 years after the first GNSS satellite was launched and less than30 years after the first GNSS system was declared fully operational, GNSS systemscontribution to environmental monitoring is evident in our daily life. Opportunisticuse of GNSS signals as remote sensing data sources is already contributing to weatherforecast and environmental hazards monitoring, including hurricanes and floods.Moreover, the upper atmosphere environment, that is affected by both space andEarth environmental conditions, is monitored using GNSS signals. Monitoring theionospheric conditions is important because it affects directly and indirectly many ofthe critical infrastructures on Earth. Scintillation, which is rapid random fluctuationsin the amplitude and phase of radio waves resulting from the signal passing throughplasma density irregularities in the ionosphere, is the most important source ofionospheric errors that affect GNSS systems in particular.In this thesis, detecting floods using special GNSS receivers and a techniqueknown as GNSS–R is discussed. Also, detecting ionospheric perturbed conditionsleading to ionospheric scintillations using another type of special GNSS receivers,known as Ionospheric Scintillation Monitoring (ISM) receivers, is discussed.For floods detection, the feasibility of using data from GNSS–R receiversmounted onboard small Unmanned Aerial Vehicles (UAVs) are investigated. Tak-ing into account the constraints imposed on/by such platforms, a signal processingmethodology that respects such constraints when processing the signals reflectedby the potential floods is implemented. The method roughly estimates the reflectedsignal strength with respect to the noise floor, and it is demonstrated that such roughestimation is capable of accomplishing the water detection task with high accuracy.Also, the importance of UAV-based multi-constellation GNSS–R receivers for ac-curate estimation of water extents is investigated. Moreover, the importance of theUAV-based GNSS–R sensor calibration is discussed. It is demonstrated that, forfloods detection, the calibration is not strictly necessary. However, for estimating theamount of reflected power and the height of the water surface (i.e extracting moreparameters of the water/floods), calibrating the sensor is necessary.For scintillation detection, the utilization of Machine Learning (ML) algorithmsfor detecting scintillation in GNSS data to overcome the known limitations ofthe scintillation detection metrics is discussed. ML techniques has demonstratedsuccess in many scientific fields including GNSS signal processing and scintillationmodelling. It is demonstrated that ML models are able to perform better than thescintillation metrics thresholds in scintillation detection. It is also demonstrated thatML models can detect scintillation in environments where interference, multipathin particular, exists. In this regard, 98% detection accuracy, 2% scintillation miss-detection and 2% scintillation false alarm is demonstrated for a model developedfor equatorial scintillation, while 95% accuracy, 5% scintillation miss detection and5% scintillation false alarm are demonstrated for high latitude phase scintillationdetection. The abilities of various ML algorithms, with different hyper-parameters,in carrying out the detection task is also investigated. It is found that baggeddecision trees give superior performance. Finally, various measurements available inionospheric scintillation monitoring records as well as in high rate post-correlationdata are investigated. For low latitude scintillation, the signal intensity measurementsat high rate (50 Hz) are essential and sufficient. On the other hand, it is found that3-minutes Total Electron Content (TEC) data are able to surpass the scintillationmetrics in detecting polar scintillations. This could open the door for unprecedentedexpansion in global scintillation monitoring by utilizing a wide range of professionalGNSS receivers, other than the ISM receivers, that are already providing TECmeasurements.

Global Navigation Satellite Systems as Signals of Opportunity for Environmental Applications: Reflectometry and Scintillation

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Global Navigation Satellite Systems as Signals of Opportunity for Environmental Applications: Reflectometry and Scintillation

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