Name
Title | ||
|---|---|---|
Indoor AoA Estimation Using Received Signal Strength Parameter and a Support Vector Machine |
Abstract | ||
|---|---|---|
This paper deals with the Angle of Arrival (AoA) estimation in Wireless Sensor Networks (WSN). AoA is one of few parameters in WSN which are crucial for obtaining the positions of each node. AoA can be estimated in many ways. Our approach is based on the measurements of the Received Signal Strength Parameter (RSSI) using omnidirectional antennas. RSSI allows us to calculate the distances or AoA between nodes. However, in real environments, RSSI measurements are corrupted by reflected signals from obstacles and, therefore, the calculated AoA's are very inaccurate. In order to decrease these effects, we propose using machine learning for indoor environments. We show that using a Support Vector Machine (SVM) significantly increases the accuracy of AoA estimations. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/IWSSIP.2019.8787321 | 2019 International Conference on Systems, Signals and Image Processing (IWSSIP) |
Keywords | Field | DocType |
angle of arrival (AoA),omnidirectional antenna,received signal strength indicator (RSSI),support vector machine (SVM),wireless sensor network (WSN) | Omnidirectional antenna,Computer vision,Antenna radiation patterns,Dipole antenna,Computer science,Support vector machine,Angle of arrival,Artificial intelligence,Signal strength,Artificial neural network,Wireless sensor network | Conference |
ISSN | ISBN | Citations |
2157-8672 | 978-1-7281-3228-0 | 0 |
PageRank | References | Authors |
0.34 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marko Malajner | 1 | 0 | 0.68 |
| Dusan Gleich | 2 | 24 | 6.92 |
| P. Planinšič | 3 | 27 | 7.70 |