Abstract
Indoor positioning system based on WiFi Round-Trip Time (RTT) measurement is believed to deliver sub-metre level accuracy with trilateration, under ideal indoor conditions. However, the performance of WiFi RTT positioning in complex, non-line-of-sight environments re-mains a research challenge.
To this end, this paper investigates the properties of WiFi RTT in several real-world indoor environments on heterogeneous smartphones. We present a large-scale real-world dataset containing both RTT and received signal strength (RSS) signal measures with correct ground-truth labels.
Our results indicated that RTT fingerprinting system delivered an accuracy below 0.75 m which was 98% better than RSS fingerprinting and 166% better than RTT trilateration, which failed to deliver sub-metre accuracy as claimed.
To this end, this paper investigates the properties of WiFi RTT in several real-world indoor environments on heterogeneous smartphones. We present a large-scale real-world dataset containing both RTT and received signal strength (RSS) signal measures with correct ground-truth labels.
Our results indicated that RTT fingerprinting system delivered an accuracy below 0.75 m which was 98% better than RSS fingerprinting and 166% better than RTT trilateration, which failed to deliver sub-metre accuracy as claimed.
| Original language | English |
|---|---|
| Number of pages | 17 |
| Publication status | Published - 12 Sept 2022 |
| Event | 17th International Conference on Location Based Services - Munich, Germany Duration: 12 Sept 2022 → 14 Sept 2022 https://conferences.lfk.lrg.tum.de/lbs2022/ |
Conference
| Conference | 17th International Conference on Location Based Services |
|---|---|
| Abbreviated title | LBS 2022 |
| Country/Territory | Germany |
| City | Munich |
| Period | 12/09/22 → 14/09/22 |
| Internet address |
Keywords
- Indoor Positioning
- WiFi Round-Trip Time
- Non-line-of-sight measure