全球导航卫星系统应用
大地基准
遥感
大地测量学
天线高度注意事项
多径传播
地质学
精密点定位
计算机科学
全球定位系统
天线(收音机)
电信
频道(广播)
作者
Cemali Altuntaş,Nursu Tunalıoğlu
标识
DOI:10.1016/j.dsp.2021.103011
摘要
Global Navigation Satellite Systems (GNSS) have been routinely used for geodetic-based survey and mapping studies such as precise point positioning, landslide, earthquake and crustal deformation monitoring, engineering surveys, in short, where accurate positioning is required. To do that, the GNSS observables should be eliminated from the error sources. Among the error sources affected to GNSS data, multipath stands for one of the largest error sources and should be removed. This multipath affects the strength of received microwave signal or signal-to-noise ratio (SNR), which is recorded at the GNSS antenna. As of now, many studies are successfully conducted to retrieve reflector height from signal-to-noise ratio (SNR) data gathered with a geodetic GNSS receiver. However, GNSS SNR data collected from a smartphone may also show a pattern for interferences of the direct and reflected signals from where the aforementioned heights are retrieved. In this study, an experimental site was setup to retrieve effective reflector height from a permanent mast attaching both smartphone with single frequency and geodetic GNSS receiver. The GNSS SNR data were gathered by the same time interval for a specific vertical height from the ground for three days and for approximately 5-h daily observation durations. The validation of the estimated reflector heights was performed by the root mean square error (RMSE) analysis. The RMSEs of estimated reflector heights for Xiaomi Mi 8 Lite and Trimble NetR9 geodetic receiver are computed as 1.9 and 3.7 cm, respectively. The initial results show that the outcomes of the analysis agree well with whether the in-situ measurements or the mean values via RMSEs. According to the performance assessments for accurate height detection and cost efficiency, single-frequency smartphones can be used to extract the reflector height from the collected raw SNR data.
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