Paper
28 April 2023 Research on fingerprint location algorithm based on stack auto-encoder network
Heng Shi, Jian Wu, Ying Cong, ChengLong Xue, YuHao Xie, YuBing Hu
Author Affiliations +
Proceedings Volume 12626, International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022); 126261F (2023) https://doi.org/10.1117/12.2674420
Event: International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022), 2022, Zhuhai, China
Abstract
With the continuous development of modern network and communication technology, in view of the people to the location service especially rising demand based on the location of the indoor positioning services, as well as the existing indoor positioning method is complex and positioning accuracy is not high question, this paper proposes a fusion from coding and bluetooth stack location fingerprinting indoor localization algorithm has high precision, The algorithm using the stack from coding network first determine the coarse position of target, and use the network to predict location for the secondary position, finally use the fingerprint matching algorithm for accurate positioning of the final, average position precision can be up to 25 cm, finally through the simulation analysis this ask the performance of the proposed algorithm, this algorithm is verified indoor location can reduce the computation complexity, It can also improve the positioning accuracy.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Heng Shi, Jian Wu, Ying Cong, ChengLong Xue, YuHao Xie, and YuBing Hu "Research on fingerprint location algorithm based on stack auto-encoder network", Proc. SPIE 12626, International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022), 126261F (28 April 2023); https://doi.org/10.1117/12.2674420
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KEYWORDS
Machine learning

Computer simulations

Neural networks

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