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EN
Nowadays, the use of multi-Global Navigation Satellite System (GNSS) has improved positioning accuracy in autonomous driving, navigation and tracking systems utilized by general users. However, signal quality in urban areas is degraded by poor satellite geometry and severe multipath errors, which may disturb up to a hundred-meter-ranging error as a consequence. In this study, the performance of several satellite selection methods in multipath mitigation was evaluated, based on the concept that better quality signals and more accurate solutions will be obtained, the more multipath signals can be excluded. Three methods were performed and compared: 1) azimuth-dependent elevation mask based on fisheye image technique, 2) receiver autonomous integrity monitoring (RAIM), and 3) signalto-noise ratio (SNR) mask in the SPP method. To examine the effect of the satellite selection methods on multipath error, the static test (single-point positioning (SPP) in real-time 1 Hz test) was performed in a multipath environment. The preliminary results showed a possible impact on improving the horizontal positioning accuracy of SPP. Among the three techniques assessed in this study, the results indicated that the SNR mask set at 36 dB-Hz in every elevation showed the most promising result. The SNR mask method could improve positioning accuracy by up to 46.80% compared to the SPP method.
2
Content available remote Improving the stochastic model for VRS network-based GNSS surveying
EN
The VRS network-based technique has become the main precise GNSS surveying method especially for medium-range baselines (approximately 20-70 km). The key concept of this approach is to use the observables of multiple reference stations to generate the network correction in the form of a virtual reference station for mitigating distance-dependent errors including atmospheric effects and orbital uncertainty at the user’s location. Numerous GNSS data processing strategies have been adopted in the functional model in order to improve both the positioning accuracy and the success of ambiguity resolution. However, it is impossible to completely model the aforementioned errors. As a result, the unmodelled residuals still remain in the virtual reference station observables when the least squares estimation is employed. An alternative approach to deal with these residuals is to construct a more realistic stochastic model whereby the variance-covariance matrix is assumed to be homoscedastic. This research aims to investigate a suitable stochastic model used for the VRS technique. The rigorous statistical method, MINQUE has been applied to estimate the variance-covariance matrix of the double-difference observables for a virtual reference station to rover baseline determination. The findings of the comparison to the equal-weight model and the satellite elevation-based model indicated that the MINQUE procedure could enhance the positioning accuracy. In addition, the reliability of ambiguity resolution is also improved.
EN
Each GNSS constellation operates its own system times; namely, GPS system time (GPST), GLONASS system time (GLONASST), BeiDou system time (BDT) and Galileo system time (GST). They could be traced back to Coordinated Universal Time (UTC) scale and are aligned to GPST. This paper estimates the receiver clock offsets to three timescales: GPST, GLONASST and BDT. The two measurement scenarios use two identical multi-GNSS geodetic receivers connected to the same geodetic antenna through a splitter. One receiver is driven by its internal oscillators and another receiver is connected to the external frequency oscillators, caesium frequency standard, kept as the Thailand standard time scale at the National Institute of Metrology (Thailand) called UTC(NIMT). The three weeks data are observed at 30 seconds sample rate. The receiver clock offsets with respected to the three system time are estimated and analysed through the geodetic technique of static Precise Point Positioning (PPP) using a data processing software developed by Wuhan University - Positioning And Navigation Data Analyst (PANDA) software. The estimated receiver clock offsets are around 32, 33 and 18 nanoseconds from GPST, GLONASST and BDT respectively. This experiment is initially stated that each timescale is inter-operated with GPST and further measurements on receiver internal delay has to be determined for clock comparisons especially the high accuracy clock at timing laboratories.
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