Five-dimensional local positioning using neural networks
| dc.contributor.author | Furufors, Fredrik | |
| dc.contributor.department | Chalmers tekniska högskola / Institutionen för data- och informationsteknik (Chalmers) | sv |
| dc.contributor.department | Chalmers University of Technology / Department of Computer Science and Engineering (Chalmers) | en |
| dc.date.accessioned | 2019-07-03T14:28:40Z | |
| dc.date.available | 2019-07-03T14:28:40Z | |
| dc.date.issued | 2017 | |
| dc.description.abstract | In this thesis, a method for real-time transmitter localization is evaluated. An existing system has acted as testbed for the evaluation. This system uses an electromagnetic transmitter and a receiver board with 16 antennas. The antenna values are used to recover the transmitters position and two angles, the five dimensions. The proposed solution is an inverse modelling feed-forward neural network, a multilayer perceptron, which is trained and evaluated with the use of the TensorFlow library. The project resulted in a purely software based estimator which requires no change to the testbed and can act as a drop in replacement for the previous algorithm. The new estimator has accomplished improvements in estimation speed (more than 100× faster), expansion of the volume in which the position can be recovered (27× larger), enlarged range of angles (10% per axis) and has improved the precision of the position estimates (error at the 95th percentile reduced to ~ 1/3 of the previous implementation). The new algorithm is a substantial improvement on the previous implementation, enabling new use cases for the system. | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12380/250055 | |
| dc.language.iso | eng | |
| dc.setspec.uppsok | Technology | |
| dc.subject | Data- och informationsvetenskap | |
| dc.subject | Computer and Information Science | |
| dc.title | Five-dimensional local positioning using neural networks | |
| dc.type.degree | Examensarbete för masterexamen | sv |
| dc.type.degree | Master Thesis | en |
| dc.type.uppsok | H | |
| local.programme | Computer science – algorithms, languages and logic (MPALG), MSc |
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