Abstract
Abstract. With the smartphone boom, positioning oneself on the Earth's surface has become something common. Everyone know how to uses their smartphone to get their location or finding their way. However, achieve centimetric accuracy on positioning still a topical issue that arouses considerable interest. Geodetic GNSS antennas are currently used for this field, but their price is incompatible with the mass market applications (autonomous cars, drones, machine automation, photogrammetry, etc.). In this paper, an approach to improve the Android smartphone positioning is presented using low-cost GNSS receiver. Requested by Syslor, a start-up working in buried networks, the society want to enhance its customer services. The purpose of this study is to present a method to reach centimetric localisation of smartphones for augmented reality and as-built 3D plans applications.
Highlights
To get accurate GNSS positioning under Android Operating System, the main challenges are to get in the same time high quality satellite observations and the ability to process data acquired by the receiver from a smartphone
The first test is best suited for GNSS measurement because it is performed in open sky
The low-cost antenna is placed on the ground and positioned with a centring disc (Figure 6) while the true values were measured with GNSS pole
Summary
To get accurate GNSS positioning under Android Operating System, the main challenges are to get in the same time high quality satellite observations and the ability to process data acquired by the receiver from a smartphone. In 2016, the release of Android Nougat marked an evolution in GNSS measurement on smartphone. This version provided for the first-time access to new functionalities dedicated to GNSS. A more realistic hybrid solution was selected It consists in using the phone as the user terminal and associating an external low-cost GNSS receiver (Atunggal et al, 2018; Madawalagama et al, 2019). These receivers have the advantage of being inexpensive and do not suffer from extreme miniaturization that minimizes performance and observation capabilities. This study will provide a better understanding of how they work and how they can be integrated into a smartphone solution
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