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Characterisation and position-aiding performance analysis of Doppler observation from android smartphones

Published online by Cambridge University Press:  28 April 2023

Zihan Peng ,
Chengfa Gao ,
Hua Zou ,
Rui Shang ,
Qi Liu  and
Wu Zhao
Zihan Peng
Affiliation:
School of Transportation, Southeast University, Nanjing, China
Chengfa Gao*
Affiliation:
School of Transportation, Southeast University, Nanjing, China
Hua Zou
Affiliation:
China Mobile (Shanghai) Industry Research Institute, Shanghai, China
Rui Shang
Affiliation:
School of Transportation, Southeast University, Nanjing, China
Qi Liu
Affiliation:
School of Transportation, Southeast University, Nanjing, China
Wu Zhao
Affiliation:
China Mobile (Shanghai) Industry Research Institute, Shanghai, China
*
*Corresponding author: Chengfa Gao; Email: gaochfa@163.com
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Abstract

It has been acknowledged that the Doppler is beneficial to the GNSS positioning of smartphones. However, analysis of Doppler precision on smartphones is insufficient. In this paper, we focus on the characteristic analysis of the raw Doppler measurement from Android smartphones. A comprehensive investigation of the Doppler was conducted. The results illustrate that the availability of Doppler is stable and higher than that of carrier measurements, which means that the Doppler-smoothed code (DSC) method is more effective. However, there is a constant bias between the Doppler and the code rate in Xiaomi MI8, which indicates that extra processing of the DSC method is necessary for this phone. Additionally, it is demonstrated that the relationship between the Doppler and C/N0 can be expressed as an exponential function, and the fitting parameters are provided. The numerical experiment in car-borne and hand-held scenes was conducted for evaluating the performance of the Doppler-aided positioning algorithm. For positioning, the improvement reaches 37 ⋅ 69%/37 ⋅ 14%/26 ⋅ 61% in the east, north and up components, respectively, after applying the Doppler aiding. For velocity estimation, the improvement reaches 29 ⋅ 62%/39 ⋅ 63%/29 ⋅ 37% in the three components, respectively.

Keywords

GNSSandroid smartphonesDopplercharacteristicaided positioning
Type
Research Article
Information
The Journal of Navigation , Volume 76 , Issue 2-3 , March 2023 , pp. 375 - 393
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Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press on behalf of The Royal Institute of Navigation

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