Abstract
Inter-system bias (ISB) will affect accuracy and processing time in integrated precise point positioning (PPP), and ISB stochastic models will largely determine the quality of ISB estimation. Thus, the impacts of four different stochastic models of ISB processing will be assessed and studied in detail to further reveal the influence of ISB in positioning. They are ISB-PW considering ISB as a piece-wise constant, ISB-RW considering ISB as random walk, ISB-AD considering ISB as an arc-dependent constant, and ISB-WN considering ISB as white noise. Together with the model without introducing ISB called ISB-OFF, i.e., five different schemes, ISB-OFF, ISB-PW, ISB-RW, ISB-AD, and ISB-WN, will be designed and tested in this study. From the results of pseudorange residuals, it can be noticed that when considering ISB, the Root-Mean-Square (RMS) of ionosphere-free combined pseudorange residuals are much smaller than without ISB (ISB-OFF). The results of convergence time and positioning accuracy analysis show that PPP performance with ISB-AD is even worse than ISB-OFF, when using the precise products from the German Research Centre for Geosciences (GFZ) named as GBM products here; while the strategies of ISB-RW, and ISB-WN achieve the best results. For the products from Wuhan University called WUM products, a completely different result is achieved. PPP with the stochastic models of ISB-PW and ISB-AD perform best. The most likely reason is the ISB stochastic models applied by the analysis centers are consistent with those used in the PPP on the user side. So, ISB-RW, or ISB-WN is recommended when GBM products are used, and for the WUM products, ISB-PW, or ISB-AD is chosen. From the statistics of PPP precision during the convergence period, it can be concluded that considering ISB also has a great improvement on combined PPP accuracy during the initialization phase.
Highlights
Along with the modernization of the Global Positioning System (GPS) [1], the revitalization of the Russian Global Navigation Satellite System (GLONASS) [2], the launch of more European Global Navigation Satellite System (Galileo) satellites [3], and the fast development of Chinese BeiDou Navigation Satellite System (BDS) [4,5], more and more satellites can be observed at one place
We will apply the precise products from GBM and WUM to validate the difference between these two kinds of products and analyze the potential influence of the different inter-system bias (ISB) estimation strategies used in different analysis centers (AC) on the positioning and convergence time
The statistical results of the other four schemes are similar, and compared to ISB-OFF, the RMS of pseudorange residuals for ISB-PW, ISB as a random-walk processing (ISB-RW), ISB as a processing-arc-dependent constant (ISB-AD), and ISB as white noise (ISB-WN) can reduce by 21.3 m (95.9%) both in static mode and kinematic mode
Summary
Along with the modernization of the Global Positioning System (GPS) [1], the revitalization of the Russian Global Navigation Satellite System (GLONASS) [2], the launch of more European Global Navigation Satellite System (Galileo) satellites [3], and the fast development of Chinese BeiDou Navigation Satellite System (BDS) [4,5], more and more satellites can be observed at one place. As for the estimation stochastic models of ISB, normally a strategy of considering ISB as an arc-dependent constant is applied in Paziewski and Wielgosz [12], Li, et al [13], Guo, et al [14], and Lou, et al [15]. Et al [9] regard ISB as a piece-wise parameter, which can increase the sample size and is good for ISB modeling and prediction Besides these two strategies, another two stochastic models can be used, which are considering ISB as white noise or as random walk. In our multi-GNSS combined processing model, we introduce an extra ISB parameter to cover the effect of the biases between the two systems, and the ISB is estimated with other unknowns using the ionospheric-free (IF) PPP processing
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