Paper
10 November 2022 Improvement of fingerprint location method based on KNN-PF algorithm
Xinyi Xue, Hao Wang, Haidong Hu, Chenkai Ma
Author Affiliations +
Proceedings Volume 12331, International Conference on Mechanisms and Robotics (ICMAR 2022); 1233134 (2022) https://doi.org/10.1117/12.2652192
Event: International Conference on Mechanisms and Robotics (ICMAR 2022), 2022, Zhuhai, China
Abstract
Fingerprint positioning is a common method of indoor positioning. The matching algorithm is an important part of determining the final positioning accuracy. How to choose a better algorithm to improve the positioning accuracy is the focus of this article. The traditional KNN algorithm is a common matching algorithm, but its positioning accuracy is not very high. Therefore, this paper proposes to select the optimal hyperparameter K through cross-validation, align to perform KNN regression, and then pass PF (particle filter) Method to optimize its results, its average positioning accuracy is improved by 23%, which has certain practical significance.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xinyi Xue, Hao Wang, Haidong Hu, and Chenkai Ma "Improvement of fingerprint location method based on KNN-PF algorithm", Proc. SPIE 12331, International Conference on Mechanisms and Robotics (ICMAR 2022), 1233134 (10 November 2022); https://doi.org/10.1117/12.2652192
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KEYWORDS
Particles

Computer simulations

Data centers

Particle filters

Signal attenuation

Databases

Pollution control

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