Joint Coordinate Optimization in Fingerprint-Based Indoor Positioning
نویسندگان
چکیده
Fingerprint-based indoor positioning uses pattern recognition algorithms (PRAs) to estimate the users’ locations in wireless local area network environments, where satellite-based methods cannot work properly. Traditionally, training phase of PRA is separately conducted for $x$ and notation="LaTeX">$y$ coordinates. However, received signal strength from access points a unique fingerprint each measured point, not coordinates separately. In this letter, we propose method jointly employ during using novel PRA-based Gaussian process regression (GPR), named 2D-GPR. Experimental results show that proposed 2D-GPR improves accuracy more than notation="LaTeX">$40cm$ limited data samples has lower calculation cost compared with conventional GPR.
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ژورنال
عنوان ژورنال: IEEE Communications Letters
سال: 2021
ISSN: ['1558-2558', '1089-7798', '2373-7891']
DOI: https://doi.org/10.1109/lcomm.2020.3047352