Ultra-wideband Fingerprinting Positioning Based on Convolutional Neural Network
| Title | Ultra-wideband Fingerprinting Positioning Based on Convolutional Neural Network |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Lei, M., Jin, M., Huang, T., Guo, Z., Wang, Q., Wu, Z., Chen, Z., Chen, X., Zhang, J. |
| Conference Name | 2020 International Conference on Computer, Information and Telecommunication Systems (CITS) |
| Date Published | Oct. 2020 |
| Publisher | IEEE |
| ISBN Number | 978-1-7281-6544-8 |
| Keywords | Acoustic Fingerprints, composability, convolutional neural nets, convolutional neural network, convolutional neural networks, fingerprint positioning methods, Fingerprint recognition, fingerprinting positioning, Global Positioning System, GPS, Human Behavior, indoor positioning system, indoor radio, precise position, precise positioning, pubcrawl, resilience, Resiliency, Robustness, satellite signals, Support vector machines, telecommunication computing, Training, ultra wideband communication, Ultra wideband technology, ultra-wideband, ultra-wideband fingerprinting positioning method, underwater acoustic communication, Wireless fidelity |
| Abstract | The Global Positioning System (GPS) can determine the position of any person or object on earth based on satellite signals. But when inside the building, the GPS cannot receive signals, the indoor positioning system will determine the precise position. How to achieve more precise positioning is the difficulty of an indoor positioning system now. In this paper, we proposed an ultra-wideband fingerprinting positioning method based on a convolutional neural network (CNN), and we collect the dataset in a room to test the model, then compare our method with the existing method. In the experiment, our method can reach an accuracy of 98.36%. Compared with other fingerprint positioning methods our method has a great improvement in robustness. That results show that our method has good practicality while achieves higher accuracy. |
| URL | https://ieeexplore.ieee.org/document/9232628 |
| DOI | 10.1109/CITS49457.2020.9232628 |
| Citation Key | lei_ultra-wideband_2020 |
- precise positioning
- Wireless fidelity
- underwater acoustic communication
- ultra-wideband fingerprinting positioning method
- ultra-wideband
- Ultra wideband technology
- ultra wideband communication
- Training
- telecommunication computing
- Support vector machines
- satellite signals
- Robustness
- Resiliency
- resilience
- pubcrawl
- Acoustic Fingerprints
- precise position
- indoor radio
- indoor positioning system
- Human behavior
- GPS
- Global Positioning System
- fingerprinting positioning
- Fingerprint recognition
- fingerprint positioning methods
- convolutional neural networks
- convolutional neural network
- convolutional neural nets
- composability