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Journal of System Simulation

Abstract

Abstract: According to the characteristics of underground environment, a fingerprint location algorithm based on dynamic fingerprint updating is proposed. FCM(Fuzzy C-Means Clustering) is used to divide the location area according to the signal distribution characteristics, and the training and learning model is established in each sub area. On the basis of FCM algorithm, a HMM(Hidden Markov Model) motion information sequence model based on the location of mobile users is proposed. The dynamic update of fingerprint database is realized by users unconsciously participating in the collection of RSSI(Received Signal Strength Indication) sequence. ANFIS(Adaptive Network-based Fuzzy Inference System) algorithm with self-learning ability is used to locate unknown nodes. The experimental results show that the accuracy of the fingerprint location algorithm based on dynamic fingerprint update can reach 1.6m, which can meet the real-time location requirements of the underground roadway.

First Page

818

Revised Date

2020-01-20

Last Page

824

CLC

TP391.9

Recommended Citation

Cui Lizhen, Wang Qiaoli, Guo Qianqian, Yang Yong. Research on Fingerprint Location Algorithm Based on Dynamic Fingerprint Update[J]. Journal of System Simulation, 2021, 33(4): 818-824.

DOI

10.16182/j.issn1004731x.joss.19-0653

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