A STATISTICAL ANALYSIS ON THE SYSTEM PERFORMANCE OF A BLUETOOTH LOW ENERGY INDOOR POSITIONING SYSTEM IN A 3D ENVIRONMENT
Since GPS tends to fail for indoor positioning purposes, alternative methods like indoor positioning systems (IPS) based on Bluetooth low energy (BLE) are developing rapidly. Generally, IPS are deployed in environments covered with obstacles such as furniture, walls, people and electronics influen...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-09-01
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| Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-2-W4/319/2017/isprs-annals-IV-2-W4-319-2017.pdf |
| Summary: | Since GPS tends to fail for indoor positioning purposes, alternative methods like indoor positioning systems (IPS) based on Bluetooth
low energy (BLE) are developing rapidly. Generally, IPS are deployed in environments covered with obstacles such as furniture, walls,
people and electronics influencing the signal propagation. The major factor influencing the system performance and to acquire optimal
positioning results is the geometry of the beacons. The geometry of the beacons is limited to the available infrastructure that can be
deployed (number of beacons, basestations and tags), which leads to the following challenge: Given a limited number of beacons,
where should they be placed in a specified indoor environment, such that the geometry contributes to optimal positioning results?
This paper aims to propose a statistical model that is able to select the optimal configuration that satisfies the user requirements in
terms of precision. The model requires the definition of a chosen 3D space (in our case 7 × 10 × 6 meter), number of beacons, possible
user tag locations and a performance threshold (e.g. required precision). For any given set of beacon and receiver locations, the
precision, internal- and external reliability can be determined on forehand. As validation, the modeled precision has been compared
with observed precision results. The measurements have been performed with an IPS of BlooLoc at a chosen set of user tag locations
for a given geometric configuration. Eventually, the model is able to select the optimal geometric configuration out of millions of
possible configurations based on a performance threshold (e.g. required precision). |
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| ISSN: | 2194-9042 2194-9050 |