
Ph.D. in Ingegneria Elettrica, Elettronica E Delle Comunicazioni , 33rd cycle (2017-2020)
Ph.D. obtained in 2021
Dissertation:
Analysis and Detection of Outliers in GNSS Measurements by Means of Machine Learning Algorithms (Abstract)
Tutors:
Fabio Dovis
Research presentation:
Video presentationProfile
Research topic
Carrier-Based Software GNSS Receiver Design
Research interests
Biography
Awards and Honors
Teaching
Teachings
Master of Science
- Satellite navigation systems. A.A. 2020/21, COMMUNICATIONS AND COMPUTER NETWORKS ENGINEERING (INGEGNERIA TELEMATICA E DELLE COMUNICAZIONI). Collaboratore del corso
Publications
Works published during the Ph.D. View all publications in Porto@Iris
- Imam, Rayan; Savas, Caner; Dovis, Fabio (2021)
Detecting Phase Scintillation at High Latitudes Using Ionospheric Scintillation Monitoring Records and Machine Learning Techniques. In: 2021 IEEE International Conference on Wireless for Space and Extreme Environments (WiSEE), Cleveland, OH, USA, 12-14 Oct. 2021, pp. 37-42. ISBN: 978-1-6654-0371-9
Contributo in Atti di Convegno (Proceeding) - Savas, C.; Falco, G.; Dovis, F. (2021)
A Comparative Performance Analysis of GPS L1 C/A, L5 Acquisition and Tracking Stages under Polar and Equatorial Scintillations. In: IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, vol. 57, pp. 227-244. ISSN 0018-9251
Contributo su Rivista - Savas, Caner (2021)
Analysis and Detection of Outliers in GNSS Measurements by Means of Machine Learning Algorithms. relatore: DOVIS, FABIO; , 33. XXXIII Ciclo, P.: 175
Doctoral Thesis - Ghobadi, H.; Savas, C.; Spogli, L.; Dovis, F.; Cicone, A.; Cafaro, M. (2020)
A Comparative Study of Different Phase Detrending Algorithms for Scintillation Monitoring. In: 33rd General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2020, Rome, Italy, 2020, pp. 1-4. ISBN: 978-9-4639-6800-3
Contributo in Atti di Convegno (Proceeding) - Dovis, F.; Imam, R.; Qin, W.; Savas, C.; Visser, H. (2020)
Opportunistic use of GNSS Signals to Characterize the Environment by Means of Machine Learning Based Processing. In: 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020, Barcelona, Spain, Spain, 4-8 May 2020, pp. 9190-9194. ISSN 1520-6149. ISBN: 978-1-5090-6631-5
Contributo in Atti di Convegno (Proceeding) - Savas, Caner; Dovis, Fabio (2019)
The Impact of Different Kernel Functions on the Performance of Scintillation Detection Based on Support Vector Machines. In: SENSORS, vol. 19, pp. 1-16. ISSN 1424-8220
Contributo su Rivista