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- W4309494413 abstract "5G millimeter wave (mmWave) signals can enable accurate positioning in vehicular networks when the base station and vehicles are equipped with large antenna arrays. However, radio-based positioning suffers from multipath signals generated by different types of objects in the physical environment. Multipath can be turned into a benefit, by building up a radio map (comprising the number of objects, object type, and object state) and using this map to exploit all available signal paths for positioning. We propose a new method for cooperative vehicle positioning and mapping of the radio environment, comprising a multiple-model probability hypothesis density filter and a map fusion routine, which is able to consider different types of objects and different fields of views. Simulation results demonstrate the performance of the proposed method." @default.
- W4309494413 created "2022-11-28" @default.
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- W4309494413 date "2019-08-26" @default.
- W4309494413 modified "2023-10-04" @default.
- W4309494413 title "5G mmWave Cooperative Positioning and Mapping using Multi-Model PHD Filter and Map Fusion" @default.
- W4309494413 doi "https://doi.org/10.48550/arxiv.1908.09806" @default.
- W4309494413 hasPublicationYear "2019" @default.
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