Title: Analysis of GNSS data quality based on Anubis and RTKLIB and single-point positioning accuracy in different environments for Android smartphones
Authors: Qiaoli Kong; Qi Bai; Tianfa Wang; Changsong Li; Yanfei Chen; Jingwei Han
Addresses: College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, 266590, China ' College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, 266590, China ' College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, 266590, China ' College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, 266590, China ' College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, 266590, China ' College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, 266590, China
Abstract: With the improvement of global navigation satellite system (GNSS) and the popularity of smart devices, location-based services based on smartphones have been developed rapidly, but there are few studies that compare the GNSS data quality and positioning ability of single-frequency smartphones (Huawei P10) and dual-frequency smartphones (Xiaomi 8 and Huawei Mate40Pro). This paper aims to analyse the GNSS data quality of each of the smartphones above using G/NUT-Anubis and RTKLIB software, and realise the single-point positioning of smartphones in open, obscured and indoor environments, respectively. The test results show that the GNSS data quality of smartphones is only a little worse than that of geodetic receiver, and the tracking abilities of the Xiaomi 8 and Huawei Mate40Pro are better than that of the Huawei P10. In open and obscured environments, the positioning accuracy of the Huawei Mate40Pro is at the metre level and higher than that of the Xiaomi 8.
Keywords: Android smartphone; raw GNSS observations; data quality analysis; G/NUT-Anubis; single-point positioning; SPP; RTKLIB.
DOI: 10.1504/IJSNET.2023.129633
International Journal of Sensor Networks, 2023 Vol.41 No.2, pp.78 - 96
Received: 20 Jun 2022
Accepted: 27 Sep 2022
Published online: 17 Mar 2023 *