技术
全球导航卫星系统应用
总电子含量
遥感
电离层
大地测量学
大地基准
计算机科学
太空天气
卫星
加权
全球定位系统
环境科学
地质学
气象学
地理
物理
电信
地球物理学
声学
天文
作者
Li Xu,Jiuping Zha,Min Li,Yunbin Yuan,Baocheng Zhang
出处
期刊:Gps Solutions
[Springer Science+Business Media]
日期:2022-09-04
卷期号:26 (4)
被引量:14
标识
DOI:10.1007/s10291-022-01329-w
摘要
The global navigation satellite system (GNSS) measurements to determine ionospheric total electron content (TEC) are mainly derived from expensive geodetic-grade receivers, which are not conducive to high-density placement. In this work, we present an analysis of the performance of ionospheric TEC determined by GNSS dual-frequency measurements derived from the smartphone, taking the Xiaomi 8 (XMI8) as an example. First, the ionospheric observable is retrieved from the code and carrier phase data using the carrier-to-code leveling technique and a new carrier-to-noise weighting strategy instead of an elevation weighting strategy, considering the characteristic of the GNSS measurements from smartphones. Then, the absolute ionospheric slant TEC (STEC) values are isolated from the ionospheric observables by modeling with the generalized trigonometric series function. The experimental data, covering over 120 h, were taken from two situations: one is the data collected by the original smartphone antenna; the other is the external geodetic-grade antenna. The TEC data obtained from the collocated geodetic-grade receiver are used as reference data to evaluate the performance of the TEC values from XMI8. Compared to the reference data, the evaluation results show that the ionospheric STEC extraction accuracy can reach total electron content unit (TECU) values of 0.17 and 0.11 under the two different situations in the continuous carrier phase satellite arc without cycle slips. In addition, the VTEC modeling accuracy is above 5 and 2 TECU in the two different situations, respectively. Thus, we concluded that consumer-level GNSS chipsets are highly potential in the future to increase the ionospheric monitoring station density due to their low costs and good data quality.
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