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• W2939934626 abstract "In this paper, a novel scheme is reported to adapt radio maps to environmental dynamics in an online fashion by combining crowdsourcing and gaussian process regression (GPR). Specifically, a Marginalized Particle Gaussian Process (MPGP) is adopted to recursively fuse crowdsourced fingerprints with an existing offline radio map. The advantages of the proposed scheme lie in the efficiency and scalability in comparison with the traditional approaches. Extensive experiments are carried out in a real scenario of nearly 1000 m <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</sup> during five months, and a comparison is made with several existing popular solutions. It is shown that the proposed scheme outperforms its counterparts in terms of both robustness and accuracy." @default.
• W2939934626 created "2019-04-25" @default.
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• W2939934626 date "2019-05-01" @default.
• W2939934626 modified "2023-09-27" @default.
• W2939934626 title "Online Radio Map Update Based on a Marginalized Particle Gaussian Process" @default.
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• W2939934626 doi "https://doi.org/10.1109/icassp.2019.8683485" @default.
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