Using crowdsourced satellite SNR measurements for 3D mapping and real-time GNSS positioning improvement
Autor: | Andrew Irish, Joao P. Hespanha, Elizabeth Belding, Upamanyu Madhow, Daniel Iland, Jason T. Isaacs |
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Rok vydání: | 2014 |
Předmět: | |
Zdroj: | S3@MobiCom |
DOI: | 10.1145/2645884.2645890 |
Popis: | Geopositioning using Global Navigation Satellite Systems (GNSS), such as the Global Positioning System (GPS), is inaccurate in urban environments due to frequent non-line-of-sight (NLOS) signal reception. This poses a major problem for mobile services that benefit from accurate urban localization, such as navigation, hyperlocal advertising, and geofencing applications. However, urban NLOS signal reception can be exploited in two ways. First, one can use satellite signal-to-noise ratio (SNR) measurements crowdsourced from mobile devices to create 3D environment maps. This is possible because, for example, the SNR of signals obstructed by buildings is lower on average than that of line-of-sight (LOS) signals. Second, in a sort of reverse process called Shadow Matching, SNR readings from a particular device at an instant in time can be compared to 3D maps to provide real-time localization improvement. In this paper we give a brief overview of how such a system works and describe a scalable, low-cost, software-only architecture that implements it. |
Databáze: | OpenAIRE |
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