Collaborative Indoor Positioning Systems: A Systematic Review

被引:66
|
作者
Pascacio, Pavel [1 ,2 ]
Casteleyn, Sven [1 ]
Torres-Sospedra, Joaquin [1 ,3 ]
Lohan, Elena Simona [2 ]
Nurmi, Jari [2 ]
机构
[1] Univ Jaume 1, Inst New Imaging Technol, Castellon de La Plana 12006, Spain
[2] Tampere Univ, Elect Engn Unit, Tampere 33014, Finland
[3] UBIK Geospatial Solut SL, Castellon de La Plana 12006, Spain
关键词
collaborative indoor positioning systems; positioning technique; positioning method; positioning technology; location-based services; systematic literature review; COOPERATIVE LOCALIZATION ALGORITHM; NODE TRACKING; NAVIGATION; MULTISENSOR; PRIVACY; FUSION; IMU;
D O I
10.3390/s21031002
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Research and development in Collaborative Indoor Positioning Systems (CIPSs) is growing steadily due to their potential to improve on the performance of their non-collaborative counterparts. In contrast to the outdoors scenario, where Global Navigation Satellite System is widely adopted, in (collaborative) indoor positioning systems a large variety of technologies, techniques, and methods is being used. Moreover, the diversity of evaluation procedures and scenarios hinders a direct comparison. This paper presents a systematic review that gives a general view of the current CIPSs. A total of 84 works, published between 2006 and 2020, have been identified. These articles were analyzed and classified according to the described system's architecture, infrastructure, technologies, techniques, methods, and evaluation. The results indicate a growing interest in collaborative positioning, and the trend tend to be towards the use of distributed architectures and infrastructure-less systems. Moreover, the most used technologies to determine the collaborative positioning between users are wireless communication technologies (Wi-Fi, Ultra-WideBand, and Bluetooth). The predominant collaborative positioning techniques are Received Signal Strength Indication, Fingerprinting, and Time of Arrival/Flight, and the collaborative methods are particle filters, Belief Propagation, Extended Kalman Filter, and Least Squares. Simulations are used as the main evaluation procedure. On the basis of the analysis and results, several promising future research avenues and gaps in research were identified.
引用
收藏
页码:1 / 39
页数:39
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