Subsidence is determined in the heart of the Central Valley using Post Processed Static and Precise Point Positioning techniques

2020 ◽  
Vol 14 (1) ◽  
pp. 113-118 ◽  
Author(s):  
Y. Facio ◽  
M. Berber

AbstractPost Processed Static (PPS) and Precise Point Positioning (PPP) techniques are not new; however, they have been refined over the decades. As such, today these techniques are offered online via GPS (Global Positioning System) data processing services. In this study, one Post Processed Static (OPUS) and one Precise Point Positioning (CSRS-PPP) technique is used to process 24 h GPS data for a CORS (Continuously Operating Reference Stations) station (P565) duration of year 2016. By analyzing the results sent by these two online services, subsidence is determined for the location of CORS station, P565, as 3–4 cm for the entire year of 2016. In addition, precision of these two techniques is determined as ∼2 cm. Accuracy of PPS and PPP results is 0.46 cm and 1.21 cm, respectively. Additionally, these two techniques are compared and variations between them is determined as 2.5 cm.

2012 ◽  
Vol 29 (3) ◽  
pp. 269-274 ◽  
Author(s):  
Byung-Kyu Choi ◽  
Kyoung-Min Roh ◽  
Sung-Ki Cho ◽  
Jong-Uk Park ◽  
Pil-Ho Park ◽  
...  

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3220
Author(s):  
Honglei Qin ◽  
Peng Liu ◽  
Li Cong ◽  
Xia Xue

Although precise point positioning (PPP) is a well-established and promising technique with the use of precise satellite orbit and clock products, it costs a long convergence time to reach a centimeter-level positioning accuracy. The PPP with ambiguity resolution (PPP-AR) technique can improve convergence performance by resolving ambiguities after separating the fractional cycle bias (FCB). Now the FCB estimation is mainly realized by the regional or global operating reference station network. However, it does not work well in the areas where network resources are scarce. The contribution of this paper is to realize an ambiguity residual constraint-based PPP with partial ambiguity resolution (PPP-PARC) under no real-time network corrections to speed up the convergence, especially when the performance of the float solution is poor. More specifically, the update strategy of FCB estimation in a stand-alone receiver is proposed to realize the PPP-PAR. Thereafter, the solving process of FCB in a stand-alone receiver is summarized. Meanwhile, the influencing factors of the ambiguity success rate in the PPP-PAR without network corrections are analyzed. Meanwhile, the ambiguity residual constraint is added to adapt the particularity of the partial ambiguity-fixing without network corrections. Moreover, the positioning experiments with raw observation data at the Global Positioning System (GPS) globally distributed reference stations are conducted to determine the ambiguity residual threshold for post-processing and real-time scenarios. Finally, the positioning performance was verified by 22 GPS reference stations. The results show that convergence time is reduced by 15.8% and 26.4% in post-processing and real-time scenarios, respectively, when the float solution is unstable, compared with PPP using a float solution. However, if the float solution is stable, the PPP-PARC method has performance similar to the float solution. The method shows the significance of the PPP-PARC for future PPP applications in areas where network resource is deficient.


2014 ◽  
Vol 14 (9) ◽  
pp. 2503-2520 ◽  
Author(s):  
V. Wirz ◽  
J. Beutel ◽  
S. Gruber ◽  
S. Gubler ◽  
R. S. Purves

Abstract. Detecting and monitoring of moving and potentially hazardous slopes requires reliable estimations of velocities. Separating any movement signal from measurement noise is crucial for understanding the temporal variability of slope movements and detecting changes in the movement regime, which may be important indicators of the process. Thus, methods capable of estimating velocity and its changes reliably are required. In this paper we develop and test a method for deriving velocities based on noisy GPS (Global Positioning System) data, suitable for various movement patterns and variable signal-to-noise-ratios (SNR). We tested this method on synthetic data, designed to mimic the characteristics of diverse processes, but where we have full knowledge of the underlying velocity patterns, before applying it to explore data collected.


Author(s):  
Sarosh Khan ◽  
Pawan Maini ◽  
Kittichai Thanasupsin

In the last few decades several car-following models have been proposed and tested using mainly vehicle location data. The use of high-precision Global Positioning System (GPS) data to test several car-following and collision constraint models is reported, with a critical evaluation of these models and proposal of a modified collision constraint formulation. GPS receivers typically report time-stamped location or position fixes and velocity. For a pair of leading and following vehicles, location and velocity data were used to examine estimates of acceleration, velocity, and headway by Pipes’s; modified Pitt’s, or FRESIM; CARSIM; and INTELSIM car-following models. The important aspects of collecting accurate GPS data are also highlighted.


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