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Sensors 2017, 17(12), 2828; doi:10.3390/s17122828

Indoors Locality Positioning Using Cognitive Distances and Directions

1,2
,
1,2,* and 1,2
1
State Key Lab for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, China
2
Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China
*
Author to whom correspondence should be addressed.
Received: 17 October 2017 / Revised: 2 December 2017 / Accepted: 2 December 2017 / Published: 7 December 2017
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [3894 KB, uploaded 7 December 2017]   |  

Abstract

Spatial relationships are crucial to spatial knowledge representation, such as positioning localities. However, minimal attention has been devoted to positioning localities indoors with locality description. Distance and direction relations are generally used when positioning localities, namely, translating descriptive localities into spatially explicit ones. We propose a joint probability function to model locality distribution to address the uncertainty of positioning localities. The joint probability function consists of distance and relative direction membership functions. We propose definitions and restrictions for the use of the joint probability function to make the locality distribution highly practical. We also evaluate the performance of our approach through indoor experiments. Test results demonstrate that a positioning accuracy of 3.5 m can be achieved with the semantically derived spatial relationships. View Full-Text
Keywords: spatial relationships; membership function; positioning localities indoors; locality description spatial relationships; membership function; positioning localities indoors; locality description
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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    Doi: sensors-238561

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Wang, Y.; Fan, H.; Chen, R. Indoors Locality Positioning Using Cognitive Distances and Directions. Sensors 2017, 17, 2828.

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