Abstract
There is a real need in the robotics and wireless sensor network (WSN) communities for the estimation of the geolocation of wireless agents. The received signal strength indicator (RSSI), a common metric in most networking hardware, has been reputed as a very unreliable method for doing the job, due to its vulnerability to environmental factors. Nevertheless, it still remains as the most prevalent estimator of distance between agents on many research projects. Multipath fading, shadowing and other effects that the environment exerts over a signal while propagating are regarded as the main cause of such vulnerability. Although some success has been obtained using RSSI outdoors where the effects are less noticeable, indoor settings remain an unconquered territory. The main motivation of this paper is to establish whether, in real time applications, the use of preprocessing techniques over partial raw collected data helps the RSSI to be a suitable estimator of distance. We propose one such technique and the results suggest that its use may indeed assist the obtainment of more accurate distance estimations while using RSSI.
| Original language | English (US) |
|---|---|
| Title of host publication | 2008 IEEE International Conference on Robotics and Automation, ICRA 2008 |
| Pages | 1537-1542 |
| Number of pages | 6 |
| DOIs | |
| State | Published - Sep 18 2008 |
| Event | 2008 IEEE International Conference on Robotics and Automation, ICRA 2008 - Pasadena, CA, United States Duration: May 19 2008 → May 23 2008 |
Other
| Other | 2008 IEEE International Conference on Robotics and Automation, ICRA 2008 |
|---|---|
| Country | United States |
| City | Pasadena, CA |
| Period | 5/19/08 → 5/23/08 |
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All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Software
- Artificial Intelligence
- Electrical and Electronic Engineering
Cite this
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Preprocessing technique to signal strength data of wireless sensor network for real-time distance estimation. / Cabrera, Flavio; Xiao, Jizhong.
2008 IEEE International Conference on Robotics and Automation, ICRA 2008. 2008. p. 1537-1542 4543420.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Preprocessing technique to signal strength data of wireless sensor network for real-time distance estimation
AU - Cabrera, Flavio
AU - Xiao, Jizhong
PY - 2008/9/18
Y1 - 2008/9/18
N2 - There is a real need in the robotics and wireless sensor network (WSN) communities for the estimation of the geolocation of wireless agents. The received signal strength indicator (RSSI), a common metric in most networking hardware, has been reputed as a very unreliable method for doing the job, due to its vulnerability to environmental factors. Nevertheless, it still remains as the most prevalent estimator of distance between agents on many research projects. Multipath fading, shadowing and other effects that the environment exerts over a signal while propagating are regarded as the main cause of such vulnerability. Although some success has been obtained using RSSI outdoors where the effects are less noticeable, indoor settings remain an unconquered territory. The main motivation of this paper is to establish whether, in real time applications, the use of preprocessing techniques over partial raw collected data helps the RSSI to be a suitable estimator of distance. We propose one such technique and the results suggest that its use may indeed assist the obtainment of more accurate distance estimations while using RSSI.
AB - There is a real need in the robotics and wireless sensor network (WSN) communities for the estimation of the geolocation of wireless agents. The received signal strength indicator (RSSI), a common metric in most networking hardware, has been reputed as a very unreliable method for doing the job, due to its vulnerability to environmental factors. Nevertheless, it still remains as the most prevalent estimator of distance between agents on many research projects. Multipath fading, shadowing and other effects that the environment exerts over a signal while propagating are regarded as the main cause of such vulnerability. Although some success has been obtained using RSSI outdoors where the effects are less noticeable, indoor settings remain an unconquered territory. The main motivation of this paper is to establish whether, in real time applications, the use of preprocessing techniques over partial raw collected data helps the RSSI to be a suitable estimator of distance. We propose one such technique and the results suggest that its use may indeed assist the obtainment of more accurate distance estimations while using RSSI.
UR - http://www.scopus.com/inward/record.url?scp=51649106868&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=51649106868&partnerID=8YFLogxK
U2 - 10.1109/ROBOT.2008.4543420
DO - 10.1109/ROBOT.2008.4543420
M3 - Conference contribution
SN - 9781424416479
SP - 1537
EP - 1542
BT - 2008 IEEE International Conference on Robotics and Automation, ICRA 2008
ER -