Pregled bibliografske jedinice broj: 1048889
Characterisation Of Multipath-Caused Commercial- Grade GPS Positioning Error In Intelligent Transport Systems (ITS)
Characterisation Of Multipath-Caused Commercial- Grade GPS Positioning Error In Intelligent Transport Systems (ITS) // Proceedings of 2019 International Symposium ELMAR / Muštra, Mario ; Vuković, Josip ; Zovko-Cihlar, Branka (ur.).
Zagreb: Institute of Electrical and Electronics Engineers (IEEE), 2019. str. 27-30 doi:10.1109/elmar.2019.8918652 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), ostalo)
CROSBI ID: 1048889 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Characterisation Of Multipath-Caused Commercial- Grade GPS Positioning Error In Intelligent Transport Systems (ITS)
Autori
Spoljar, Darko ; Crnjaric-Zic, Nelida ; Lenac, Kristijan ; Perinovic, Valter
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), ostalo
Izvornik
Proceedings of 2019 International Symposium ELMAR
/ Muštra, Mario ; Vuković, Josip ; Zovko-Cihlar, Branka - Zagreb : Institute of Electrical and Electronics Engineers (IEEE), 2019, 27-30
ISBN
978-1-7281-2182-6
Skup
62nd International Symposium ELMAR-2020
Mjesto i datum
Zadar, Hrvatska, 14.09.2020. - 15.09.2020
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Positioning error ; Multipath characterisation ; ITS
Sažetak
The constant increase in the use of Global Navigation Satellite Systems (GNSS) in different technical and economic areas requires the determination of the position with the required accuracy for each individual application. In a user environment where the so called multipaths when receiving the signal from the satellite comes to their effect on the error of determining the position. In this paper, we present the influence of multiple paths on the position determination error in intelligent transport systems using the Autoregressive Model (AR). The influence of multipath on position determination error shows significant deviation from normal distribution and requires more complex AR models or introduction of complex Autoregressive Moving Average (ARMA) models or stochastic models.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
