Vehicular Teamwork for Better Positioning.

Alireza Famili, Vladyslav Slyusar, Yun Ho Lee,Angelos Stavrou

2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)(2023)

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摘要
Recent developments in the autonomous vehicle industries have increased the significance of accurate positioning. Popular techniques for localization include the Global Positioning System (GPS). However, owing to the presence of obstructions, GPS signals are unavailable in dense urban environments. Moreover, in indoor environments (such as a parking garage below the ground), GPS signals are inaccessible to users. In this article, we introduce a novel technique for accurate indoor vehicular positioning. The first step in our proposed system is localization based on received signal strength (RSS) fingerprints of 5G New Radio (NR) downlink signals. Furthermore, to compensate for the high susceptibility of RSS fingerprinting techniques in varying environments, we propose a real-time collaborative localization scheme based on 5G sidelink device-to-device (D2D) communication. We develop extensive test campaigns to assess the efficacy of our proposed two-step scheme. According to test results, our proposed algorithm outperforms scenarios that rely solely on 5G RSS fingerprints.
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关键词
vehicular positioning,5G RSS fingerprinting,D2D cooperative positioning,RTT,indoor localization
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