Employing Ray-Tracing and Least-Squares Support Vector Machines for Localisation †
Abstract
:1. Introduction
2. Experimental Setup and Methodology
2.1. Ray Tracing
2.2. Assumptions
- Channel reciprocity
- Network deployment and capability
- Noise
2.3. Localisation Algorithms Used for Comparison
2.4. Data Pre-Processing
2.5. Least-Square Support Vector Machines
2.6. Direct LSSVM Localisation Method
2.6.1. Training and Estimation
2.6.2. Post-Processing and Outlier Removal
2.7. Localisation Performance
2.8. Environments Considered
2.9. Performance Comparisons
3. Results
3.1. Results for the Direct Method
3.2. Comparison with TOA/AOA
3.3. Comparison with TDOA
4. Discussion
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
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Chitambira, B.; Armour, S.; Wales, S.; Beach, M. Employing Ray-Tracing and Least-Squares Support Vector Machines for Localisation. Sensors 2018, 18, 4059. https://doi.org/10.3390/s18114059
Chitambira B, Armour S, Wales S, Beach M. Employing Ray-Tracing and Least-Squares Support Vector Machines for Localisation. Sensors. 2018; 18(11):4059. https://doi.org/10.3390/s18114059
Chicago/Turabian StyleChitambira, Benny, Simon Armour, Stephen Wales, and Mark Beach. 2018. "Employing Ray-Tracing and Least-Squares Support Vector Machines for Localisation" Sensors 18, no. 11: 4059. https://doi.org/10.3390/s18114059