Garrett Seepersad's research while affiliated with York University and other places

... Aggrey et al. [19] compared PPP performance for four smartphones under static and kinematic experiments, and the MI 8 achieved 40 cm rms in the horizontal direction, which was far better than other single-frequency smart devices. In addition, similar performance can be also seen from numerous recent contributions with real-time and final products [20][21][22][23][24]. Continuing this research, recent studies prove that dual-frequency smartphones can provide lane-level navigation processed with both RTK and PPP technologies in realistic driving environments [25,26], and the solutions can be further improved with the aid of smartphone native Inertial Measurement Unites (IMUs) [27,28]. ...

... Aggrey et al. [19] compared PPP performance for four smartphones under static and kinematic experiments, and the MI 8 achieved 40 cm rms in the horizontal direction, which was far better than other single-frequency smart devices. In addition, similar performance can be also seen from numerous recent contributions with real-time and final products [20][21][22][23][24]. Continuing this research, recent studies prove that dual-frequency smartphones can provide lane-level navigation processed with both RTK and PPP technologies in realistic driving environments [25,26], and the solutions can be further improved with the aid of smartphone native Inertial Measurement Unites (IMUs) [27,28]. ...

... On the other hand, PPP based on uncombined observables with a lower noise level provides alternative solutions. Liu et al. proposed a joint-processing model for multi-GNSS in which the inter-system biases and inter-frequency biases are carefully considered [11]; Pan et al. investigated the positional contribution of combined systems to accelerate convergence and initialization time of PPP in kinematic and static mode [12]; Aggrey and Bisnath studied the atmospheric influences on positioning and proposed an improved approach to model ionospheric delays for multi-GNSS PPP [13]. Psychas et al. investigated the potential of multi-GNSS positioning on a smartphone, and the results indicated that the accuracy of the horizontal components is improved more than 40% by combining GPS and Galileo observations as compared to the GPS alone case [14]. ...

... These accuracies and limited purchase costs allow for the establishment of more measurement points in surveying and geodetic networks [20] and the discovery of other application areas, such as ionosphere monitoring [21]. The single frequency was a limitation for PPP applications [22]; therefore, double differences for long vectors were preferred to obtain high accuracies [23]. The newer two-frequency receivers showed a horizontal error of 3 mm and a vertical error of 8 mm in relative positioning [24]. ...

... Therefore, one must ask, "Is PPP AR essential for reliable, decimeter-level AIV positioning?" [141]. Despite those problems, there is no doubt that multi-GNSS, multi-frequency UD, and uncombined observations are the future direction of AIV applications [115]. ...

... The relative positioning accuracy of smartphones in short 20 min sessions can reach the horizontal decimeter accuracy and vertical component accuracies exceeding 2 m [13]. Precise Point Positioning [14] results based on mobile phones may even provide accuracies of 37 and 51 cm for horizontal and vertical components, respectively [15]. The use of the observation quality information of the observations provided by smartphones can also reduce the positioning quality [16]. ...

... In PPP approach, the resolution of integer ambiguity is not possible because observations are contaminated by equipment delays. Ambiguity resolution in PPP, so called PPP-AR, needs the equipment delays within the GPS observations to be mitigated (Bertiger et al. 2010;Laurichesse et al. 2009;Seepersad and Bisnath 2017). With the development of the PPP-AR technique, the positioning accuracy has increased and the convergence time has been shortened (Guo et al. 2021;Li et al. 2011;Loyer et al. 2012;Li and Zhang 2012). ...

... These techniques have significantly matured over the years, and research has demonstrated connections between the various models in use (Teunissen and Khodabandeh 2015). Initial efforts have also shown that a combination of these products preserving the integer characteristics of ambiguities at the user end is possible (Seepersad et al. 2016). ...

... It is important that the user-end adopts the algorithms and models consistent with those adopted for the computations of the biases and corrections at the network-end. "Mixing" of different conventions may lead to incorrect AR or even positioning failure (Seepersad and Bisnath 2016). For example, there are three different commonly used PPP-AR models-UPD/FCB, IRC and DSC-as mentioned earlier. ...

... Figure 7 summarizes the performance for each station by looking at the convergence time to 2.5 cm rather than 10 cm, as was done for Figure 6. The reason behind this choice is to analyze the possibility of achieving the (N)RTK requirement of near-instantaneous 2.5 cm horizontal error at 1σ (Bisnath et al., 2013). Figure 7 shows that the RTK requirement that was set is reached for many stations. ...