Pregled bibliografske jedinice broj: 1204622
Statistical properties of mid-latitude TEC time series observed during rapidly developing short- term geomagnetic storms: A contribution to GNSS- related TEC predictive model development
Statistical properties of mid-latitude TEC time series observed during rapidly developing short- term geomagnetic storms: A contribution to GNSS- related TEC predictive model development // Proc of 2022 3rd URSI Atlantic and Asia Pacific Radio Science Meeting (AT-AP-RASC) / Prof. Peter Van Daele (ur.).
Lahti: URSI, 2022. str. 1-4 doi:10.23919/AT-AP-RASC54737.2022.9814229 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1204622 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Statistical properties of mid-latitude TEC time
series observed during rapidly developing short-
term geomagnetic storms: A contribution to GNSS-
related TEC predictive model development
Autori
Sikirica, Nenad ; Zhen, Weinmin ; Filjar, Renato
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proc of 2022 3rd URSI Atlantic and Asia Pacific Radio Science Meeting (AT-AP-RASC)
/ Prof. Peter Van Daele - Lahti : URSI, 2022, 1-4
Skup
3rd URSI Atlantic and Asia Pacific Radio Science Meeting (AT-AP-RASC 2022)
Mjesto i datum
Las Palmas de Gran Canaria, Španjolska, 29.05.2022. - 03.06.2022
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Total Electron Content (TEC) ; time series ; statistical properties ; satellite navigation ; geomagnetic storm
Sažetak
Total Electron Content (TEC) affects GNSS positioning accuracy due to its effects on GNSS pseudorange measurement. GNSS resilience against the ionospheric effects requires improved accuracy of TEC predictive model. Here a contribution to the subject of self-adaptive positioning environment-aware TEC predictive model development is provided trough statistical analysis of mid- latitude TEC time series observed during rapidly developing short-term geomagnetic storms. Statistical properties of TEC sets and time series are examined to address similarities in range, variability, and information content in order to establish rapidly developing short-term geomagnetic storms as a separate class of the ionospheric event cases, with potential to degrade GNSS positioning accuracy. Results of the analysis show cases of rapidly developing short-term geomagnetic storm share similar statistical properties, notably Shannon entropy and spike index, of TEC observations, which renders them eligible to be addressed with a common TEC prediction model to rise GNSS resilience against the ionospheric effects.
Izvorni jezik
Engleski
Znanstvena područja
Matematika, Elektrotehnika, Računarstvo, Zrakoplovstvo, raketna i svemirska tehnika, Informacijske i komunikacijske znanosti
POVEZANOST RADA
Ustanove:
Tehnički fakultet, Rijeka,
Veleučilište Hrvatsko zagorje Krapina
