针对提高北极地区GNSS地理信息服务能力及北极地区GNSS研究现状较少等问题,本文对北极地区8个IGS基准站的GNSS数据进行质量评估。首先提出了对北极地区进行GNSS数据评估的重要性与TEQC软件对GNSS数据处理的优势,然后下载北极地区8个IGS...针对提高北极地区GNSS地理信息服务能力及北极地区GNSS研究现状较少等问题,本文对北极地区8个IGS基准站的GNSS数据进行质量评估。首先提出了对北极地区进行GNSS数据评估的重要性与TEQC软件对GNSS数据处理的优势,然后下载北极地区8个IGS基准站2023整年的观测数据,编写Linux批处理脚本,完成对批量数据质量评估的批处理,进而提取S文件中重要的数据质量指标,最后分析数据有效率、多路径效应误差与周跳比,对指标较差的测站提出相应的解决方案。In response to the issues of improving the geographic information service capabilities of GNSS in the Arctic region and the limited research status of GNSS in the Arctic region, this article conducts a quality evaluation of GNSS data from 8 IGS reference stations in the Arctic region. Firstly, this article highlights the importance of GNSS data evaluation in the Arctic region and the advantages of TEQC software in GNSS data processing. Then, we download observation data of 8 IGS stations in the Arctic region for the entire year 2023 and write batch script under Linux environment to complete batch processing of data quality evaluation, so as to extract important data quality indicators from the Summary (S) file. Finally, we analyze data efficiency, multipath effect errors, and cycle slip ratio, and proposes solutions for stations with poor indicators.展开更多
文摘针对提高北极地区GNSS地理信息服务能力及北极地区GNSS研究现状较少等问题,本文对北极地区8个IGS基准站的GNSS数据进行质量评估。首先提出了对北极地区进行GNSS数据评估的重要性与TEQC软件对GNSS数据处理的优势,然后下载北极地区8个IGS基准站2023整年的观测数据,编写Linux批处理脚本,完成对批量数据质量评估的批处理,进而提取S文件中重要的数据质量指标,最后分析数据有效率、多路径效应误差与周跳比,对指标较差的测站提出相应的解决方案。In response to the issues of improving the geographic information service capabilities of GNSS in the Arctic region and the limited research status of GNSS in the Arctic region, this article conducts a quality evaluation of GNSS data from 8 IGS reference stations in the Arctic region. Firstly, this article highlights the importance of GNSS data evaluation in the Arctic region and the advantages of TEQC software in GNSS data processing. Then, we download observation data of 8 IGS stations in the Arctic region for the entire year 2023 and write batch script under Linux environment to complete batch processing of data quality evaluation, so as to extract important data quality indicators from the Summary (S) file. Finally, we analyze data efficiency, multipath effect errors, and cycle slip ratio, and proposes solutions for stations with poor indicators.
