Multi-fingerprint Information Optimization Indoor Positioning System Based on Random Forest and Particle Filter
Pages 795 - 799
Abstract
With the development of positioning technology, research hotspots have gradually shifted from the previous GPS-based satellite positioning to today's indoor positioning. And various indoor positioning technologies have gradually matured with the progress of the times. Bluetooth technology occupies an important position in the research of indoor positioning due to its excellent robustness and outstanding cost performance. Based on random forest and particle filter, this paper proposes an original indoor positioning algorithm for multi-fingerprint information optimization. On the basis of the multi-fingerprint information, the random forest is utilized to analyze and cluster the BLE logarithmic distance path attenuation model to obtain positioning data, which is further supplemented with the particle filter algorithm based on maximum likelihood, to achieve a precision optimization over 40%.
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- Multi-fingerprint Information Optimization Indoor Positioning System Based on Random Forest and Particle Filter
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November 2020
1202 pages
ISBN:9781450387811
DOI:10.1145/3443467
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Association for Computing Machinery
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Published: 01 February 2021
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EITCE 2020
EITCE 2020: 2020 4th International Conference on Electronic Information Technology and Computer Engineering
November 6 - 8, 2020
Xiamen, China
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EITCE '20 Paper Acceptance Rate 214 of 441 submissions, 49%;
Overall Acceptance Rate 508 of 972 submissions, 52%
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