A “near” relation enhanced multi-sourced data fusion indoor positioning method

doi:10.11947/j.AGCS.2024.20230019

Acta Geodaetica et Cartographica Sinica ›› 2024, Vol. 53 ›› Issue (1): 118-125.doi: 10.11947/j.AGCS.2024.20230019

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A “near” relation enhanced multi-sourced data fusion indoor positioning method

WANG Yankun^1,2,3, FAN Hong⁴, FAN Yong^3,5, LI Xiaoming³, WANG Weixi³, GUO Renzhong³

1. Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen 518034, China;
2. Internet of Things Research Institute, Shenzhen Polytechnic, Shenzhen 518055, China;
3. Research Institute for Smart Cities, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518061, China;
4. State Key Lab for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, China;
5. School of Artifcial Intelligence, Shenzhen Polytechnic, Shenzhen 518055, China

Received:2023-01-29 Revised:2023-08-24 Published:2024-02-06
Supported by:
The National Natural Science Foundation of China (Nos. 42001389; 41971341); The Spacial Project in Key fields of Universities in Guangdong Province (No. 2022ZDZX3071); Open Research Fund Program of Key Laboratory of Urban Land Resources Monitoring and Simulation (No. KF-2022-07-024); Post-doctoral Later-stage Foundation Project of Shenzhen Polytechnic (Nos. 6021271017K; 6023271011K); Project of Shenzhen Polytechnic (Nos. 6022312062K; 6023310002K)

Abstract

Abstract: Aiming at the problem of the single traditional indoor positioning mode, a “near” relation in locality description enhanced multi-sourced data fusion voice interaction method for indoor positioning is proposed. Firstly, the characteristics of “near” spatial relationship are studied. The probability membership function of “near” spatial relationship is established based on “stolen area” and the shortest distance for indoor environment. Secondly, the fingerprint information of each reference point, the distance and motion information between reference points are collected. The process of indoor locality description is modeled based on the hidden Markov model, and the user location is predicted by the Viterbit algorithm. Finally, the experiment show that the average positioning accuracy of the proposed method is 1.88 m, and the positioning accuracy can reach 2.12 m within 80%.

Key words: “near” spatial relation, multi-source data fusion, indoor positioning, voice interaction

CLC Number:

P228

WANG Yankun, FAN Hong, FAN Yong, LI Xiaoming, WANG Weixi, GUO Renzhong. A “near” relation enhanced multi-sourced data fusion indoor positioning method[J]. Acta Geodaetica et Cartographica Sinica, 2024, 53(1): 118-125.

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A “near” relation enhanced multi-sourced data fusion indoor positioning method

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