Outdoor Visible Light Positioning Using Artificial Neural Networks for Autonomous Vehicle Application
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Electronic versions
DOI
In this paper, a novel outdoor 2-D vehicular visible light positioning (VLP) using a linear array of streetlights and artificial neural network (ANN) is proposed. The classical position methods which are mostly based on triangulation will not work with the linear array of the street light. Hence, we proposed a spatial diversity receiver with ANN to overcome the collinearity condition. The proposed system is simulated for a realistic outdoor condition and provides an accurate positioning with an average RMS error of 0.53m.
Keywords
- Artificial neural network, outdoor positioning, receiver diversity, visible light positioning
| Original language | English |
|---|---|
| Title of host publication | 2020 12th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP) |
| Place of Publication | United States |
| Publisher | IEEE |
| Pages | 1-4 |
| Number of pages | 4 |
| ISBN (print) | 9781728160511 |
| DOIs | |
| Publication status | Published - 10 Nov 2020 |
| Externally published | Yes |