Abstract
The paper presents the analysis of single-point GPS positioning results obtained from smartphones, using code observations on the L1 and L5 frequencies. In this research we used two Huawei P30 Pro mobile phones and one geodetic receiver (Javad Alpha) acting as the reference receiver. Smartphones were placed at an equal distance of 0.5 m from this receiver. Such a close distance was specially planned by the authors in order to achieve identical observation conditions. Thus, it was possible to compare the accuracy of GPS positioning using pseudoranges on the L1 and L5 frequencies for individual observation epochs. The analysis was carried out from static GPS positioning, using the results from the open-source RTKLib software. In general, the usefulness of code measurements on the L5 frequency to determine the GPS position made it possible to increase the accuracy by several times with respect to the positions determined using the C/A code on the L1 frequency. Average errors of horizontal and vertical coordinates were about 70 % lower for the GPS solution using the L5 code observations than using the L1 code observations. Based on statistical analysis, a horizontal accuracy of about 0.45 m and vertical accuracy of about 1.8 m (STDEV) with only five GPS satellites may be obtained using a smartphone with L5 code observations.
-
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
-
Research funding: None declared.
-
Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
References
1. Ashkenazi, V, Hill, CJ, Ochieng, WY, Nagle, J. Wide-area differential GPS: a performance study. Navigation 1993;40:297–319. https://doi.org/10.1002/j.2161-4296.1993.tb02310.x.Search in Google Scholar
2. Kremer, GT, Kalafus, RM, Loomis, PV, Reynolds, JC. The effect of selective availability on differential GPS corrections. Navigation 1990;37:39–52. https://doi.org/10.1002/j.2161-4296.1990.tb01533.x.Search in Google Scholar
3. Tien Bui, D, Tran, CT, Pradhan, B, Revhaug, I, Seidu, R. iGeoTrans–a novel iOS application for GPS positioning in geosciences. Geocarto Int 2015;30:202–17.10.1080/10106049.2014.902114Search in Google Scholar
4. Alves, D, Dalbelo, L, Monico, J, Shimabukuro, M. First Brazilian real time network DGPS through the Internet: development, application and availability analyses. J Geod Sci 2012;2:1–7. https://doi.org/10.2478/v10156-011-0018-7.Search in Google Scholar
5. Specht, C, Smolarek, L, Pawelski, J, Specht, M, Dąbrowski, P. Polish DGPS system: 1995–2017–study of positioning accuracy. Pol Marit Res 2019;26:15–21. https://doi.org/10.2478/pomr-2019-0021.Search in Google Scholar
6. Odijk, D, Wanninger, L. Differential positioning. In: Springer handbook of global navigation satellite systems. Springer handbooks. Cham: Springer; 2017.10.1007/978-3-319-42928-1_26Search in Google Scholar
7. Purfürst, T. Evaluation of static autonomous GNSS positioning accuracy using single-dual-and tri-frequency smartphones in forest canopy environments. Sensors 2022;22:1289. https://doi.org/10.3390/s22031289.Search in Google Scholar PubMed PubMed Central
8. Banville, S, Van Diggelen, F. Precision GNSS for everyone precise positioning using raw GPS measurements from android smart phones. Cleveland: North Coast Media ATTN: GPS World; 2016.Search in Google Scholar
9. Pirazzi, G, Mazzoni, A, Biagi, L, Crespi, M. Preliminary performance analysis with a GPS+Galileo enabled chipset embedded in a smartphone. In: Proceedings of the ION GNSS+, September 25–29, 2017. Portland, Oregon, USA: Institute of Navigation; 2017:101–15 pp.Search in Google Scholar
10. Realini, E, Caldera, S, Pertusini, L, Sampietro, D. Precise GNSS positioning using smart devices. Sensors 2017;17:2434. https://doi.org/10.3390/s17102434.Search in Google Scholar PubMed PubMed Central
11. Zhang, X, Tao, X, Zhu, F, Shi, X, Wang, F. Quality assessment of GNSS observations from an Android N smartphone and positioning performance analysis using time differenced filtering approach. GPS Solut 2018;22:70. https://doi.org/10.1007/s10291-018-0736-8.Search in Google Scholar
12. Robustelli, U, Baiocchi, V, Pugliano, G. Assessment of dual frequency GNSS observations from a Xiaomi Mi8 Android smartphone and positioning performance analysis. Electronics 2019;8:91. https://doi.org/10.3390/electronics8010091.Search in Google Scholar
13. Pirazzi, G, Mazzoni, A, Biagi, L, Crespi, M. Preliminary performance analysis with a GPS+Galileo enabled chipset embedded in a smartphone. In: Proceedings of the 30th international technical meeting of the satellite division of the institute of navigation (ION GNSS+ 2017), Portland, OR, USA, 25–29 September; 2017:101–15 pp.10.33012/2017.15260Search in Google Scholar
14. Paziewski, J, Sieradzki, R, Baryla, R. Signal characterization and assessment of code GNSS positioning with low-power consumption smartphones. GPS Solut 2019;23:98. https://doi.org/10.1007/s10291-019-0892-5.Search in Google Scholar
15. Hakansson, M. Characterization of GNSS observations from a Nexus 9 android tablet. GPS Solut 2018;23:21. https://doi.org/10.1007/s10291-018-0818-7.Search in Google Scholar
16. Liu, W, Shi, X, Zhu, F, Tao, X, Wang, F. Quality analysis of multi-GNSS raw observations and a velocity-aided positioning approach based on smartphones. Adv Space Res 2019;63:2358–77. https://doi.org/10.1016/j.asr.2019.01.004.Search in Google Scholar
17. Gao, R, Xu, L, Zhang, B, Liu, T. Raw GNSS observations from Android smartphones: characteristics and short-baseline RTK positioning performance. Meas Sci Technol 2021;32:084012. https://doi.org/10.1088/1361-6501/abe56e.Search in Google Scholar
18. Tomaštík, J, Chudá, J, Tunák, D, Chudý, F, Kardoš, M. Advances in smartphone positioning in forests: dual-frequency receivers and raw GNSS data. For Int J For Res 2020;94:292–310. https://doi.org/10.1093/forestry/cpaa032.Search in Google Scholar
19. Uradziński, M, Bakuła, M. Assessment of static positioning accuracy using low-cost smartphone GPS devices for geodetic survey points’ determination and monitoring. Appl Sci 2020;10:5308. https://doi.org/10.3390/app10155308.Search in Google Scholar
20. Wanninger, L, Heelbarth, A. GNSS code and carrier phase observations of a Huawei P30 smartphone: quality assessment and centimeter-accurate positioning. GPS Solut 2020;24:1–9.10.1007/s10291-020-00978-zSearch in Google Scholar
21. Romero-Andrade, R, Zamora-Maciel, A, Uriarte-Adrian, J, Pivot, F, Trejo-Soto, ME. Comparative analysis of precise point positioning processing technique with GPS low-cost in different technologies with academic software. Measurement 2019;136:337–44. https://doi.org/10.1016/j.measurement.2018.12.100.Search in Google Scholar
22. Semler, Q, Mangin, L, Moussaoui, A, Semin, E. Development of a low-cost centimetric GNSS positioning solution for Android applications. Int Arch Photogram Rem Sens Spatial Inf Sci 2019;42:XLII-2/W17. https://doi.org/10.5194/isprs-archives-xlii-2-w17-309-2019.Search in Google Scholar
23. Dabove, P, Di Pietra, V. Single-Baseline RTK positioning using dual-frequency GNSS receivers inside smartphones. Sensors 2019;19:4302. https://doi.org/10.3390/s19194302.Search in Google Scholar PubMed PubMed Central
24. Sun, W, Li, Y, Duan, S. Xiaomi Mi 8 smartphone GNSS data quality analysis and single-frequency RTK positioning performance evaluation. IET Radar, Sonar Navig 2020;14:1410–6. https://doi.org/10.1049/iet-rsn.2020.0083.Search in Google Scholar
25. Darugna, F, Wübbena, J, Ito, A, Wübbena, T, Wübbena, G, Schmitz, M. RTK and PPP-RTK using smartphones: from short-baseline to long-baseline applications. In: Proceedings of the 32nd International technical meeting of the satellite division of the institute of navigation (ION GNSS+ 2019). Hyatt Regency Miami, Miami, Florida; 2019:3932–45 pp.10.33012/2019.17078Search in Google Scholar
26. Lachapelle, G, Gratton, P. GNSS precise point positioning with Android smartphones and comparison with high performance receivers. In: Proceedings of the 2019 IEEE international conference on signal, information and data processing (ICSIDP), Chongqing, China, 11–13 December; 2019.10.1109/ICSIDP47821.2019.9173062Search in Google Scholar
27. Tomaštík, J, Varga, M. Practical applicability of processing static, short-observation-time raw GNSS measurements provided by a smartphone under tree vegetation. Measurement 2021;178:109397. https://doi.org/10.1016/j.measurement.2021.109397.Search in Google Scholar
28. Specht, C, Dabrowski, PS, Pawelski, J, Specht, M, Szot, T. Comparative analysis of positioning accuracy of GNSS receivers of Samsung Galaxy smartphones in marine dynamic measurements. Adv Space Res 2019;63:3018–28. https://doi.org/10.1016/j.asr.2018.05.019.Search in Google Scholar
29. Fei, Y, Xueqi, H, Lidan, X, Yongrui, W. Construction and accuracy analysis of a BDS/GPS-Integrated positioning algorithm for forests. Croat J For Eng 2021;42:321–35. https://doi.org/10.5552/crojfe.2021.1105.Search in Google Scholar
30. Blum, R, Bischof, R, Sauter, U, Foeller, J. Tests of reception of the combination of GPS and GLONASS signals under and above forest canopy in the Black Forest, Germany, using choke ring antennas. Int J For Eng 2016;27:2–14. https://doi.org/10.1080/14942119.2015.1122945.Search in Google Scholar
31. Hasegawa, H, Yoshimura, T. Estimation of GPS positional accuracy under different forest conditions using signal interruption probability. J For Res 2007;12:32–6. https://doi.org/10.1007/s10310-006-0245-4.Search in Google Scholar
32. Hasegawa, H, Yoshimura, T. Application of dual-frequency GPS receivers for static surveying under tree canopies. J For Res 2003;8:103–10. https://doi.org/10.1007/s103100300012.Search in Google Scholar
33. Weaver, SA, Ucar, Z, Bettinger, P, Merry, K. How a GNSS receiver is held may affect static horizontal position accuracy. PLoS One 2015;10:e0124696. https://doi.org/10.1371/journal.pone.0124696.Search in Google Scholar PubMed PubMed Central
34. Ransom, M, Rhynold, J, Bettinger, P. Performance of mapping-grade GPS receivers in southeastern forest conditions. RURALS 2010;5:2.Search in Google Scholar
35. Uzodinma, VN, Nwafor, U. Degradation of GNSS accuracy by multipath and tree canopy distortions in a school environment: a recent study. Asian J Appl Sci 2021;4:68–77.10.9734/bpi/ciees/v4/9395DSearch in Google Scholar
36. Third-Generation GNSS Location Hub with Dual Frequency Support. Documentation on BCM47755 chipset. Broadcom Inc [Online]. https://www.broadcom.com/products/wireless/gnss-gps-socs/bcm47755 [Accessed 17 Jul 2023].Search in Google Scholar
37. Xiaomi Mi 8 documentation and user manual. https://www.manualdevices.com/xiaomi-mi-8-specification-and-user-manual/ [Accessed 17 Jul 2023].Search in Google Scholar
38. Guo, L, Wang, F, Sang, J, Lin, X, Gong, X, Zhang, W. Characteristics analysis of raw multi-GNSS measurement from Xiaomi Mi 8 and positioning performance improvement with L5/E5 frequency in an urban environment. Rem Sens 2020;12:744. https://doi.org/10.3390/rs12040744.Search in Google Scholar
39. Zangenehnejad, F, Gao, Y. GNSS smartphones positioning: advances, challenges, opportunities, and future perspectives. Satell Navig 2021;2:24. https://doi.org/10.1186/s43020-021-00054-y.Search in Google Scholar PubMed PubMed Central
40. Paziewski, J, Fortunato, M, Mazzoni, A, Odolinski, R. An analysis of multi-GNSS observations tracked by recent Android smartphones and smartphone-only relative positioning results. Measurement 2021;175:109162. https://doi.org/10.1016/j.measurement.2021.109162.Search in Google Scholar
41. Robustelli, U, Paziewski, J, Pugliano, G. Observation quality assessment and performance of GNSS standalone positioning with code pseudoranges of dual-frequency android smartphones. Sensors 2021;21:2125. https://doi.org/10.3390/s21062125.Search in Google Scholar PubMed PubMed Central
42. Paziewski, J. Recent advances and perspectives for positioning and applications with smartphone GNSS observations. Meas Sci Technol 2020;31:091001. https://doi.org/10.1088/1361-6501/ab8a7d.Search in Google Scholar
43. Li, G, Geng, J. Android multi-GNSS ambiguity resolution in the case of receiver channel-dependent phase biases. J Geodyn 2022;96:72. https://doi.org/10.1007/s00190-022-01656-3.Search in Google Scholar
44. Miao, W, Li, B, Gao, Y. The superiority of multi-GNSS L5/E5a/B2a frequency signals in smartphones: stochastic modeling, ambiguity resolution, and RTK positioning. IEEE Internet Things J 2023;10:7315–26. https://doi.org/10.1109/JIOT.2022.3228769.Search in Google Scholar
45. Yoon, D, Kee, C, Seo, J, Park, B. Position accuracy improvement by implementing the DGNSS-CP algorithm in smartphones. Sensors 2016;16:910. https://doi.org/10.3390/s16060910.Search in Google Scholar PubMed PubMed Central
46. Weng, D, Gan, X, Chen, W, Ji, S, Lu, Y. A new DGNSS positioning infrastructure for android smartphones. Sensors 2020;20:487. https://doi.org/10.3390/s20020487.Search in Google Scholar PubMed PubMed Central
47. Pepe, M, Costantino, D, Vozza, G, Alfio, VS. Comparison of two approaches to GNSS positioning using code pseudoranges generated by smartphone device. Appl Sci 2021;11:4787. https://doi.org/10.3390/app11114787.Search in Google Scholar
48. Kaplan, ED, Hegarty, CJ. Understanding GPS: principles and application, 2nd ed. Boston, MA, USA: Artech House; 2006.Search in Google Scholar
49. Klobuchar, JA. Ionospheric time-delay algorithm for single-frequency GPS users. IEEE Trans Aero Electron Syst 1987;AES-23:325–31. https://doi.org/10.1109/taes.1987.310829.Search in Google Scholar
50. Hoque, MM, Jakowski, N. An alternative ionospheric correction model for global navigation satellite systems. J Geodyn 2015;89:391–406. https://doi.org/10.1007/s00190-014-0783-z.Search in Google Scholar
51. Yang, C, Guo, J, Geng, T, Zhao, Q, Jiang, K, Xie, X, et al.. Assessment and comparison of broadcast ionospheric models: NTCM-BC, BDGIM, and Klobuchar. Rem Sens 2020;12:1215. https://doi.org/10.3390/rs12071215.Search in Google Scholar
52. ARINC Research Corporation. IS-GPS-200G, global positioning system directorate systems engineering and integration interface specification. El Segundo, CA, USA: ARINC Research Corporation; 2012.Search in Google Scholar
53. Bakota, M, Kos, S, Mrak, Z, Brčić, D. A new approach for improving GNSS geodetic position by reducing residual tropospheric error (RTE) based on surface meteorological data. Rem Sens 2023;15:162. https://doi.org/10.3390/rs15010162.Search in Google Scholar
54. Subirana, JS, Zornoza, JMJ, Hernández-Pajares, M. GNSS data processing volume I: fundamentals and algorithms acknowledgements. Leiden, The Netherlands: ESA Communications ESTE; 2013.Search in Google Scholar
55. Jin, SP, Cardellach, E, Xie, F. GNSS atmospheric and multipath delays. In: GNSS remote sensing, vol 19. Dordrecht, The Netherlands: Springer; 2014:17–30 pp.10.1007/978-94-007-7482-7_2Search in Google Scholar
56. Hopfield, HS. Two-quartic tropospheric refractivity profile for correcting satellite data. J Geophys Res 1969;74:4487–99. https://doi.org/10.1029/jc074i018p04487.Search in Google Scholar
57. Saastamoinen, J. Contributions to the theory of atmospheric refraction. Bull Geod 1972;105:279–98. https://doi.org/10.1007/bf02521844.Search in Google Scholar
58. Saastamoinen, J. Atmospheric correction for the troposphere and stratosphere in radio ranging satellites. In: Geophysical monograph series, vol 15. Washington, DC, USA: American Geophysical Union; 1972:247–51 pp.10.1029/GM015p0247Search in Google Scholar
59. Feng, P, Li, F, Yan, J, Zhang, F, Barriot, J-P. Assessment of the accuracy of the saastamoinen model and VMF1/VMF3 mapping functions with respect to ray-tracing from radiosonde data in the framework of GNSS meteorology. Rem Sens 2020;12:3337. https://doi.org/10.3390/rs12203337.Search in Google Scholar
60. RTKLib ver. 2.4.2 manual. 2013. https://www.rtklib.com/rtklib_document.htm [Accessed 17 Jul 2023].Search in Google Scholar
© 2023 Walter de Gruyter GmbH, Berlin/Boston
