Name
Abstract | ||
|---|---|---|
In this paper, we describe a novel position-recognition method that uses passive acoustic signals from two previously installed speakers (passive acoustic sensing) and active acoustic signals from a smartphone's loudspeakers (active acoustic sensing). In passive acoustic sensing, a locus of positions for the smartphone can be calculated from the measured time difference of arrival from the two installed speakers. In active acoustic sensing, a chirp signal is transmitted from the speakers of the smartphone, and the distance to the side wall is measured from the propagation time of arrival at its microphone. We can obtain the smartphone position from our proposed model equations by combining these two results. In our experiments, we installed speakers at intervals of 10 m along a corridor and estimated the smartphone position at several places. From these results, we obtained 90th percentile errors of less than 0.224 m for 2-D positioning. We found that multipaths from the side wall were causing the positioning error in passive acoustic sensing, and the variance of the positioning error using the top microphone which was omnidirectional was smaller than the bottom one. When we introduced a weighting based on the result of the active acoustic sensing and the difference in the performance between microphones, the 90th percentile errors were reduced to less than 0.134 m. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/IPIN.2018.8533764 | 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN) |
Keywords | Field | DocType |
active and passive acoustic sensing,TDoA,smart-phone,microphone | Omnidirectional antenna,Computer vision,Synchronization,Artificial intelligence,Chirp,Multilateration,Engineering,A-weighting,Loudspeaker,Propagation time,Microphone | Conference |
ISSN | ISBN | Citations |
2162-7347 | 978-1-5386-5636-5 | 0 |
PageRank | References | Authors |
0.34 | 7 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hiroaki Murakami | 1 | 0 | 1.69 |
| Masanari Nakamura | 2 | 10 | 2.19 |
| Shoma Yamasaki | 3 | 0 | 0.68 |
| Hiromichi Hashizume | 4 | 200 | 25.02 |
| Masanori Sugimoto | 5 | 775 | 95.39 |