Abstract
With the increasing interests on received signal strength (RSS) fingerprint-based Wi-Fi localization, the requirement of recording reliable and accurate RSS fingerprints for radio map construction becomes a significant concern. The neighbor matching and Bayesian estimation is recognized as the two most representative algorithms for RSS fingerprint-based indoor Wi-Fi localization. To guarantee the accuracy performance of neighbor matching and Bayesian estimation algorithms, we introduce several method to eliminate RSS sample noise for the sake of improving the distance dependency of Wi-Fi RSS fingerprints.
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CITATION STYLE
Zhou, M., Bulgantamir, O., & Wang, Y. (2018). Highly-available localization techniques in indoor Wi-Fi Environment: A comprehensive survey. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST (Vol. 251, pp. 460–469). Springer Verlag. https://doi.org/10.1007/978-3-030-00557-3_45
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