一种“附近”空间关系增强的多源融合室内定位方法

doi:10.11947/j.AGCS.2024.20230019

测绘学报 ›› 2024, Vol. 53 ›› Issue (1): 118-125.doi: 10.11947/j.AGCS.2024.20230019

一种“附近”空间关系增强的多源融合室内定位方法

王彦坤^1,2,3, 樊红⁴, 樊勇^3,5, 李晓明³, 王伟玺³, 郭仁忠³

1. 自然资源部城市国土资源监测与仿真重点试验室, 广东深圳 518034;
2. 深圳职业技术学院物联网研究院, 广东深圳 518055;
3. 深圳大学建筑与城市规划学院智慧城市研究院, 广州深圳 518061;
4. 武汉大学测绘遥感信息工程国家重点试验室, 湖北武汉 430072;
5. 深圳职业技术学院人工智能学院, 广东深圳 518055

收稿日期:2023-01-29 修回日期:2023-08-24 发布日期:2024-02-06
通讯作者: 樊勇 E-mail:fanyong@szpt.edu.cn
作者简介:王彦坤(1988-),男,博士,特聘副研究员,研究方向为室内导航与定位、空间认知。E-mail:yankun.wang@whu.edu.cn
基金资助:
国家自然科学基金(42001389;41971341);广东省普通高校重点领域专项(2022ZDZX3071);自然资源部城市国土资源监测与仿真重点试验室开放基金资助课题(KF-2022-07-024);深圳职业技术学院博士后出站后期资助项目(6021271017K;6023271011K);深圳职业技术学院项目(6022312062K;6023310002K)

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)

摘要/Abstract

摘要： 针对传统室内定位模式单一,结合室内位置描述中常用的“附近”空间关系,融合多传感器数据,本文提出一种“附近”空间关系增强的多源融合语音交互室内定位方法。首先,研究“附近”空间关系特征,针对室内环境,建立基于“窃取面积”和最短距离的“附近”空间关系的概率密度函数;其次,采集每个参考节点的指纹信息及节点间的距离和运动信息,基于隐马尔可夫模型对室内位置描述定位过程建模,通过维比特算法预测用户位置;最终,通过实际场景对本方法验证,本文提出的方法平均定位精度在1.88 m,80%的情况下定位精度可以达到2.12 m。

关键词: “附近”空间关系, 多源数据融合, 室内定位, 语音交互

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

中图分类号:

P228

王彦坤, 樊红, 樊勇, 李晓明, 王伟玺, 郭仁忠. 一种“附近”空间关系增强的多源融合室内定位方法[J]. 测绘学报, 2024, 53(1): 118-125.

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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一种“附近”空间关系增强的多源融合室内定位方法

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

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