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Design And Implementation Of Indoor Positioning System Based On IBeacon

Posted on:2019-06-20Degree:MasterType:Thesis
Country:ChinaCandidate:J X QinFull Text:PDF
GTID:2428330590975442Subject:Software engineering
Abstract/Summary:PDF Full Text Request
With the rapid development of location-based services,positioning technology has received more and more attention as the key to overcome space obstacle and support life.With high positioning accuracy and wide coverage,Global positioning system and wireless cellular network positioning system meet people's outdoor positioning needs.However,due to the occlusion of buildings,these two positioning technologies are seriously attenuated in indoor environment,which can not meet people's normal indoor location service needs.With the low power consumption,wide coverage and fast propagation speed,the indoor positioning technology based on low energy bluetooth has attracted wide attention and become a research focus in the field of indoor positioning.Due to the more corners and obstacles of the indoor environment,and the frequent movement of people,the multipath fading is serious when the bluetooth signal is transmitted indoors,making the indoor positioning accuracy based on the received signal strength low.In order to improve the positioning accuracy,this paper designs an indoor positioning system based on iBeacon.The system not only improves the positioning accuracy from the location algorithm optimization,but also filters the received signal and mobile positioning results,thus achieving high precision positioning effect.First,based on the kalman filtering algorithm,the collected iBeacon signal is filtered to reduce the signal noise.Secondly,the weights of the triangular weighted centroid algorithm are improved to improve the positioning accuracy.Finally,apply the extended kalman filter to mobile positioning results,improving the stability of mobile positioning results.After the study and simulation of positioning system technology,we realize an indoor positioning system based on iBeacon with Texas instruments CC2640 software and hardware.Through the system performance testing in a 187.5 square meter laboratory,the average positioning error of the system is 1.5866 meter,which can meet the requirements of the general indoor scene,such as office,home,shopping mall,underground parking lot garage and so on.
Keywords/Search Tags:iBeacon, indoor positioning, Kalman filtering, Triangle weighted centroid algorithm, Extended Kalman filtering
PDF Full Text Request
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