Lehtola Ville V, Söderholm Stefan, Koivisto Michelle, Montloin Leslie
Finnish Geospatial Research Institute FGI, National Land Survey, PO Box 52, 00520 Helsinki, Finland.
ITC faculty, EOS Department, University of Twente, PO Box 217, 7500 AE Enschede, The Netherlands.
Sensors (Basel). 2019 Jul 9;19(13):3018. doi: 10.3390/s19133018.
GNSS receiver data crowdsourcing is of interest for multiple applications, e.g., weather monitoring. The bottleneck in this technology is the quality of the GNSS receivers. Therefore, we lay out in an introductory manner the steps to estimate the performance of an arbitrary GNSS receiver via the measurement errors related to its instrumentation. Specifically, we do not need to know the position of the receiver antenna, which allows also for the assessment of smartphone GNSS receivers having integrated antennas. Moreover, the method is independent of atmospheric errors so that no ionospheric or tropospheric correction services provided by base stations are needed. Error models for performance evaluation can be calculated from receiver RINEX (receiver independent exchange format)data using only ephemeris corrections. For the results, we present the quality of different receiver grades through parametrized error models that are likely to be helpful in stochastic modeling, e.g., for Kalman filters, and in assessing GNSS receiver qualities for crowdsourcing applications. Currently, the typical positioning precision for the latest smartphone receivers is around the decimeter level, while for a professional-grade receiver, it is within a few millimeters.
全球导航卫星系统（GNSS）接收机数据众包技术在多个应用领域都备受关注，例如气象监测。该技术的瓶颈在于GNSS接收机的质量。因此，我们以一种介绍性的方式阐述了通过与接收机仪器相关的测量误差来估计任意GNSS接收机性能的步骤。具体而言，我们无需知道接收机天线的位置，这也使得对集成天线的智能手机GNSS接收机进行评估成为可能。此外，该方法独立于大气误差，因此无需基站提供的电离层或对流层校正服务。性能评估的误差模型可以仅使用星历校正从接收机RINEX（接收机独立交换格式）数据中计算得出。对于结果，我们通过参数化误差模型展示了不同接收机等级的质量，这些模型可能有助于随机建模，例如用于卡尔曼滤波器，以及评估众包应用中的GNSS接收机质量。目前，最新款智能手机接收机的典型定位精度约为分米级，而专业级接收机的定位精度在几毫米以内。
