Abstract
The location estimation in sensor networks is of great current interest. A general approach to location estimation is to gather Time-of-Arrival (TOA) measurements from a number of nodes and to estimate a target location. The two major sources of range measurement errors in geolocation techniques are measurement error and Non-Line-of-Sight (NLOS) error. NLOS errors caused by blocking of direct paths have been considered as one of serious issues in the location estimation. Therefore, Iterative Minimum Residual (IMR) method, which identifies NLOS nodes and removes them from the data set used for localization, has been proposed. IMR improves location estimation precision in comparison with the technique that does not identify and remove NLOS nodes. However, IMR needs a lot of calculation to identify NLOS nodes. In this paper, we propose a low complexity localization algorithm based on NLOS node identification using minimum subset for NLOS environments. We evaluate our proposed algorithm by computer simulation. We show that the proposed method achieves almost the same root mean square error (RMSE) as the conventional method with lower complexity.
| Original language | English |
|---|---|
| Title of host publication | GLOBECOM - IEEE Global Telecommunications Conference |
| Pages | 5389-5393 |
| Number of pages | 5 |
| DOIs | |
| Publication status | Published - 2008 |
| Event | 2008 IEEE Global Telecommunications Conference, GLOBECOM 2008 - New Orleans, LA, United States Duration: 2008 Nov 30 → 2008 Dec 4 |
Other
| Other | 2008 IEEE Global Telecommunications Conference, GLOBECOM 2008 |
|---|---|
| Country | United States |
| City | New Orleans, LA |
| Period | 08/11/30 → 08/12/4 |
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ASJC Scopus subject areas
- Electrical and Electronic Engineering
Cite this
Low complexity localization algorithm based on NLOS node identification using minimum subset for NLOS environments. / Fujita, Takahiro; Ohtsuki, Tomoaki.
GLOBECOM - IEEE Global Telecommunications Conference. 2008. p. 5389-5393 4698804.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Low complexity localization algorithm based on NLOS node identification using minimum subset for NLOS environments
AU - Fujita, Takahiro
AU - Ohtsuki, Tomoaki
PY - 2008
Y1 - 2008
N2 - The location estimation in sensor networks is of great current interest. A general approach to location estimation is to gather Time-of-Arrival (TOA) measurements from a number of nodes and to estimate a target location. The two major sources of range measurement errors in geolocation techniques are measurement error and Non-Line-of-Sight (NLOS) error. NLOS errors caused by blocking of direct paths have been considered as one of serious issues in the location estimation. Therefore, Iterative Minimum Residual (IMR) method, which identifies NLOS nodes and removes them from the data set used for localization, has been proposed. IMR improves location estimation precision in comparison with the technique that does not identify and remove NLOS nodes. However, IMR needs a lot of calculation to identify NLOS nodes. In this paper, we propose a low complexity localization algorithm based on NLOS node identification using minimum subset for NLOS environments. We evaluate our proposed algorithm by computer simulation. We show that the proposed method achieves almost the same root mean square error (RMSE) as the conventional method with lower complexity.
AB - The location estimation in sensor networks is of great current interest. A general approach to location estimation is to gather Time-of-Arrival (TOA) measurements from a number of nodes and to estimate a target location. The two major sources of range measurement errors in geolocation techniques are measurement error and Non-Line-of-Sight (NLOS) error. NLOS errors caused by blocking of direct paths have been considered as one of serious issues in the location estimation. Therefore, Iterative Minimum Residual (IMR) method, which identifies NLOS nodes and removes them from the data set used for localization, has been proposed. IMR improves location estimation precision in comparison with the technique that does not identify and remove NLOS nodes. However, IMR needs a lot of calculation to identify NLOS nodes. In this paper, we propose a low complexity localization algorithm based on NLOS node identification using minimum subset for NLOS environments. We evaluate our proposed algorithm by computer simulation. We show that the proposed method achieves almost the same root mean square error (RMSE) as the conventional method with lower complexity.
UR - http://www.scopus.com/inward/record.url?scp=67249142026&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=67249142026&partnerID=8YFLogxK
U2 - 10.1109/GLOCOM.2008.ECP.1029
DO - 10.1109/GLOCOM.2008.ECP.1029
M3 - Conference contribution
AN - SCOPUS:67249142026
SN - 9781424423248
SP - 5389
EP - 5393
BT - GLOBECOM - IEEE Global Telecommunications Conference
ER -