The estimation of receiver code bias for MyRTKnet stations
Khamdan S.S.a, Musa T.A.a, Wijaya D.D.b, Buhari S.M.a
a Geomatics Innovation Research Group, Faculty of Geoinformation and Real Estate, Universiti Teknologi Malaysia, Johor, 81310, Malaysia
b Geodesy Research Group, Bandung Institute of Technology, Bandung, Indonesia
Abstract
© Published under licence by IOP Publishing Ltd.This paper presents the estimation of receiver code bias of Global Positioning System (GPS) continuously operating reference stations (CORS) over Malaysian region, MyRTKnet stations. In this study, we used the Bernese software and adopted the algorithm from IONOLAB method to estimate the receiver code bias (RCB). It has been found that the RCB from Bernese and IONOLAB show a good correlation with RCB from the International GNSS Service (IGS) analysis centre with R2 values are within 0.3 ns to 0.7 ns and 0.6 ns to 0.9 ns, respectively. The estimation of RCB for MyRTKnet shows that there are no latitudinal dependencies of the RCB values. It has been found that 99% of the receivers have standard deviation below than 1 ns for both methods. It also found that both methods can provide reliable RCBs value as the mean vertical total electron content (VTEC) computed using RCBs from both methods shows a similar trend and fluctuation from IGS global ionospheric maps (GIM). Hence, it is suggested that further studies can be carried out using both methods to study the variations of RCB for a longer period to improve total electron content (TEC) estimation.
Author keywords
BERNESE softwares,Continuously operating reference stations,Global ionospheric maps,Good correlations,Malaysians,Standard deviation,Total electron content,Vertical total electron contents
Indexed keywords
Funding details
We are grateful to Department of Survey and Mapping Malaysia (DSMM) for providing the MyRTKnet observation data, the IGS and CODE for providing the GPS observation data and IONEX files for GIM. This work has been supported by the Research Grant University (Grant Number: Q.J130000.2526.19H39) and Potential Academic Staff Research Grant (Grant Number:Q.J130000.2726.02K96).