2020
DOI: 10.1080/00396265.2020.1860869
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Assessment of the GNSS PPP performance using ultra-rapid and rapid products from different analysis centres

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Cited by 4 publications
(2 citation statements)
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“…Even though actual NRT processing schemes for LEO missions are likely to differ in the specific choice of start times and arc length, the above scheme is considered generally representative and suitable to highlight the performance achievable with sub-daily observation arcs and (near-) real-time GNSS orbit and clock data. To better assess the HAS-based POD quality, we also generate NRT solutions using the WUM0MGXULA ultra-rapid multi-GNSS orbit and clock products provided by the IGS analysis center of Wuhan University (Ma et al 2017;Ogutcu and Farhan 2022). The ultra-rapid products comprise 24 h of observed orbit and clock data followed by a 24 h prediction and are generated 24 times a day with one-hour latency after the end of the observed part.…”
Section: Near Real-time Podmentioning
confidence: 99%
“…Even though actual NRT processing schemes for LEO missions are likely to differ in the specific choice of start times and arc length, the above scheme is considered generally representative and suitable to highlight the performance achievable with sub-daily observation arcs and (near-) real-time GNSS orbit and clock data. To better assess the HAS-based POD quality, we also generate NRT solutions using the WUM0MGXULA ultra-rapid multi-GNSS orbit and clock products provided by the IGS analysis center of Wuhan University (Ma et al 2017;Ogutcu and Farhan 2022). The ultra-rapid products comprise 24 h of observed orbit and clock data followed by a 24 h prediction and are generated 24 times a day with one-hour latency after the end of the observed part.…”
Section: Near Real-time Podmentioning
confidence: 99%
“…Hence, an alternate approach to the RTS might be considered by utilising ultra-rapid products to ensure positioning uninterruptedly (El-Mowafy et al., 2017). The ultra-rapid products are used in a variety of studies, including near-time troposphere estimation (Satirapod et al., 2011; Hadaś et al., 2013), precise timing (Cerretto et al., 2012), clock estimation (Cao et al., 2022), examination of dynamic displacements (Yigit et al., 2020), earthquake analysis (Shu et al., 2020), time transfer (Chen et al., 2022), real-time PPP and SPP applications (Elsobeiey and Al-Harbi, 2016; Bahadur and Nohutcu, 2021; Bahadur, 2022; Geng et al., 2022; Jiang et al., 2022; Jiao and Song, 2022; Ogutcu and Farhan, 2022).…”
Section: Introductionmentioning
confidence: 99%