LOS/NLOS detection for UWB signals: A comparative study using experimental data

In this paper the problem of detecting the channel state between LOS and NLOS conditions is addressed using UWB signals. A new distribution-based identification approach is proposed and its performance is compared with that of other classic schemes. To this purpose experimental data collected in realistic environments have been used.

[1]  Kaveh Pahlavan,et al.  Indoor geolocation in the absence of direct path , 2006, IEEE Wireless Communications.

[2]  Moe Z. Win,et al.  Ranging With Ultrawide Bandwidth Signals in Multipath Environments , 2009, Proceedings of the IEEE.

[3]  H.V. Poor,et al.  Nonparametric nonline-of-sight identification , 2003, 2003 IEEE 58th Vehicular Technology Conference. VTC 2003-Fall (IEEE Cat. No.03CH37484).

[4]  Kaveh Pahlavan,et al.  Neural Network Assisted Identification of the Absence of Direct Path in Indoor Localization , 2007, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[5]  Ismail Güvenç,et al.  NLOS Identification and Mitigation for UWB Localization Systems , 2007, 2007 IEEE Wireless Communications and Networking Conference.

[6]  Y. Jay Guo,et al.  Non-line-of-sight detection based on TOA and signal strength , 2008, 2008 IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications.

[7]  Moe Z. Win,et al.  Nonparametric Obstruction Detection for UWB Localization , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.

[8]  N.B. Mandayam,et al.  Decision theoretic framework for NLOS identification , 1998, VTC '98. 48th IEEE Vehicular Technology Conference. Pathway to Global Wireless Revolution (Cat. No.98CH36151).

[9]  Robert A. Scholtz,et al.  Ranging in a dense multipath environment using an UWB radio link , 2002, IEEE J. Sel. Areas Commun..

[10]  Kaveh Pahlavan,et al.  Identification of the Absence of Direct Path in Indoor Localization Systems , 2007, 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications.

[11]  Y. Jay Guo,et al.  Statistical NLOS Identification Based on AOA, TOA, and Signal Strength , 2009, IEEE Transactions on Vehicular Technology.

[12]  Moe Z. Win,et al.  The Effect of Cooperation on UWB-Based Positioning Systems Using Experimental Data , 2008, EURASIP J. Adv. Signal Process..

[13]  Genevieve Baudoin,et al.  A new low complexity NLOS identification approach based on UWB energy detection , 2009, 2009 IEEE Radio and Wireless Symposium.

[14]  Abdelaziz Ouldali,et al.  Joint TOA Estimation and NLOS Identification for UWB Localization Systems , 2009, 2009 Third International Conference on Sensor Technologies and Applications.

[15]  Sinan Gezici,et al.  Ultra-wideband Positioning Systems: Theoretical Limits, Ranging Algorithms, and Protocols , 2008 .

[16]  Chia-Chin Chong,et al.  NLOS Identification and Weighted Least-Squares Localization for UWB Systems Using Multipath Channel Statistics , 2008, EURASIP J. Adv. Signal Process..

[17]  G.B. Giannakis,et al.  Localization via ultra-wideband radios: a look at positioning aspects for future sensor networks , 2005, IEEE Signal Processing Magazine.

[18]  Moe Z. Win,et al.  Cooperative Localization in Wireless Networks , 2009, Proceedings of the IEEE.

[19]  R. M. Buehrer,et al.  Non-line-of-sight identification in ultra-wideband systems based on received signal statistics , 2007 .