Emulating the Smartphone GNSS Receiver to Understand and Analyze the Anomalies in RTK Positioning using GNSS Raw Measurements

被引:0
|
作者
Sharma, Himanshu [1 ]
Schuetz, Andreas [1 ]
Pany, Thomas [1 ]
机构
[1] Univ Bundeswehr Munchen, Inst Space Technol & Space Applicat ISTA, Fac Aerosp Engn, D-85577 Neubiberg, Germany
关键词
D O I
10.33012/2019.16712
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
With the release of Android N, Google announced the availability of GNSS Raw data from the mobile phone. This opens a broader perspective for research, analysis, and enhancement of the positioning quality in mobile phones. With increasing applications based upon augmented reality, e-banking, e-health, etc., there is a rapid increase in the demand for precise positioning using the existing architecture of mobile devices. On one hand, error sources such as ionospheric error and multipath mitigation tend to degrade the quality of precise positioning in mobile phones. On the other hand, cycle slip introduced due to weaker carrier-phase signal makes the positioning in mobile phone code-phase dependent only. Now with the availability of GNSS raw data, researchers are getting the opportunity to analyze and develop new concepts to enhance the carrier-phase positioning into a mobile phone. The approach presented in this paper is to emulate the smartphone and understand the effect of inducing noise in Pseudorange and Carrier phase artificially. The GNSS data recorded from smartphone directly cannot be manipulated to analyze the role of e.g. cycle slip in positioning accuracy quantitatively. Secondly, due to the hardware limitation, tracking inside the smartphone cannot be controlled which makes it difficult for researchers to play round with the GNSS data. Based upon the statistical analysis performed on the code and carrier residual from the smartphone, a high quality GNSS data was degraded. Results presented in the paper clearly indicates that the degradation of positioning accuracy due to the presence of noise introduced in the Carrier phase and Pseudorange. The first section gives user an understanding with state of the art positioning technique which is currently used in smartphones. Section 2 will give detailed description about data logging setup and techniques for inducing artifacts for emulating smartphone. In the following section results and analysis with different scenarios are discussed. In the final section paper will conclude the future possibilities and the extension of the work.
引用
收藏
页码:577 / 582
页数:6
相关论文
共 50 条
  • [21] Relative Positioning in Remote Areas Using a GNSS Dual Frequency Smartphone
    Magalhaes, Americo
    Bastos, Luisa
    Maia, Dalmiro
    Goncalves, Jose Alberto
    SENSORS, 2021, 21 (24)
  • [22] Smartphone Positioning Enhancement Using Several GNSS Satellite Selection Techniques
    ElKhalea, Mohamed F.
    Hendy, Hossam M.
    Kamel, Ahmed M.
    Arafa, Ibrahim I.
    Abosekeen, Ashraf
    2022 5TH INTERNATIONAL CONFERENCE ON COMMUNICATIONS, SIGNAL PROCESSING, AND THEIR APPLICATIONS (ICCSPA), 2022,
  • [23] Using AsteRxi GNSS/MEMS IMU Receiver in a Container Positioning System
    Vander Kuylen, L.
    Leyssens, J.
    Van Meerbergen, G.
    2010 IEEE-ION POSITION LOCATION AND NAVIGATION SYMPOSIUM PLANS, 2010, : 1179 - 1186
  • [24] A Robust Android Gnss Rtk Positioning Scheme Using Factor Graph Optimization
    Geng, Jianghui
    Long, Chiyu
    Li, Guangcai
    IEEE SENSORS JOURNAL, 2023, 23 (12) : 13280 - 13291
  • [25] Raw GNSS observations from Android smartphones: characteristics and short-baseline RTK positioning performance
    Gao, Rui
    Xu, Li
    Zhang, Baocheng
    Liu, Teng
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2021, 32 (08)
  • [26] GNSS RECEIVER'S CALIBRATION METHOD FOR RTK MEASUREMENTS BASED ON ASG-EUPOS NETWORK
    Rachon, Lidia
    Nykiel, Grzegorz
    Wrona, Maciej
    GEOCONFERENCE ON INFORMATICS, GEOINFORMATICS AND REMOTE SENSING, VOL II, 2014, : 301 - 306
  • [27] Multi-GNSS precise point positioning with next-generation smartphone measurements
    Aggrey, John
    Bisnath, Sunil
    Naciri, Nacer
    Shinghal, Ganga
    Yang, Sihan
    JOURNAL OF SPATIAL SCIENCE, 2020, 65 (01) : 79 - 98
  • [28] PrNet: A Neural Network for Correcting Pseudoranges to Improve Positioning With Android Raw GNSS Measurements
    Weng, Xu
    Ling, K. V.
    Liu, Haochen
    IEEE INTERNET OF THINGS JOURNAL, 2024, 11 (14): : 24973 - 24983
  • [29] Precise Positioning with Machine Learning based Kalman Filter using GNSS/IMU Measurements from Android Smartphone
    Han, Kahee
    Lee, Subin
    Song, Young-Jin
    Lee, Hak-Beom
    Park, Dong-Hyuk
    Won, Jong-Hoon
    PROCEEDINGS OF THE 34TH INTERNATIONAL TECHNICAL MEETING OF THE SATELLITE DIVISION OF THE INSTITUTE OF NAVIGATION (ION GNSS+ 2021), 2021, : 3094 - 3102
  • [30] Assessment of the Steering Precision of a UAV along the Flight Profiles Using a GNSS RTK Receiver
    Lewicka, Oktawia
    Specht, Mariusz
    Specht, Cezary
    REMOTE SENSING, 2022, 14 (23)