Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/133615
DC FieldValueLanguage
dc.contributor地政系
dc.creator甯方璽
dc.creatorNing, Fang-Shii
dc.creatorLi, Yi-Shan
dc.date2018-12
dc.date.accessioned2021-01-19T03:36:21Z-
dc.date.available2021-01-19T03:36:21Z-
dc.date.issued2021-01-19T03:36:21Z-
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/133615-
dc.description.abstractCurrent mainstream navigation and positioning equipment, intended for providing accurate positioning signals, comprise global navigation satellite systems, maps, and geospatial databases. Although global navigation satellite systems have matured and are widespread, they cannot provide effective navigation and positioning services in covered areas or areas lacking strong signals, such as indoor environments. To solve the problem of positioning in environments lacking satellite signals and achieve cost-effective indoor positioning, this study aimed to develop an inexpensive indoor positioning program, in which the positions of users were calculated by pedestrian dead reckoning (PDR) using the built-in accelerometer and gyroscope in a mobile phone. In addition, the corner and linear calibration points were established to correct the positions with the map assistance. Distance, azimuth, and rotation angle detections were conducted for analyzing the indoor positioning results. The results revealed that the closure accuracy of the PDR positioning was enhanced by more than 90% with a root mean square error of 0.6 m after calibration. Ninety-four percent of the corrected PDR positioning results exhibited errors of <1 m, revealing a desk-level positioning accuracy. Accordingly, this study successfully combined mobile phone sensors with map assistance for improving indoor positioning accuracy.
dc.format.extent8036616 bytes-
dc.format.mimetypeapplication/pdf-
dc.relationSensors, Vol.18, No.12, pp.4285:1-18
dc.subjectindoor positioning ; mobile phone sensors ; pedestrian dead reckoning (PDR) ; map assistance
dc.titleLow-Cost Indoor Positioning Application Based on Map Assistance and Mobile Phone Sensors
dc.typearticle
dc.identifier.doi10.3390/s18124285
dc.doi.urihttps://doi.org/10.3390/s18124285
item.fulltextWith Fulltext-
item.openairetypearticle-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextrestricted-
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