1 NLOS Identification Using a Hybrid ToA-Signal Strength Algorithm for Underwater Acoustic Localization By : Roee Diamant, Hwee-Pink Tan and Lutz Lampe.

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1 NLOS Identification Using a Hybrid ToA-Signal Strength Algorithm for Underwater Acoustic Localization By : Roee Diamant, Hwee-Pink Tan and Lutz Lampe University of British Columbia (UBC), Institute of InfoComm Research * *

Outline The problem of NLOS identification in underwater acoustic localization Channel Model and basic assumptions An algorithm for obstacle NLOS classification Sea trial results 2

3 The Problem of NLOS in Localization  Underwater acoustic attenuation models are hard to find -> Localization is mostly based on ToA distance estimation  Most existing underwater acoustic localization schemes, e.g., [1-5], implicitly assume that localization messages are received based on line- of-sight (LOS) acoustic links  Therefore, localization algorithms only consider ToA measurement noise (affected by e.g., time-synchronization, multipath, nodes motions)  However, obstacles in the channel may cause nonline-of-sight (NLOS) scenarios in which only echoes of the transmitted signal arrive at the receiver (Obstacle NLOS) If not identified, Obstacle NLOS link considerably reduces localization accuracy

System Model and Assumptions Obstacle NLOS System Model NLOS ClassificationSea trial results 4

System Model and Assumptions (2) Obstacle NLOS System Model NLOS ClassificationSea trial results 5 We expect considerable difference between ToA and signal strength distance estimations in an Obstacle NLOS link Distance to the reflecting surface and to the destination

NLOS Classification Obstacle NLOS System Model NLOS ClassificationSea trial results 6 Efficacy of the algorithm relies on the validity of the assumption that the TS+SL component is much larger than the effects of measurement noise or attenuation model inaccuracies.

Performance Analysis Obstacle NLOS System Model NLOS ClassificationSea trial results 7 Distance measurement noise variance “True” distance

Simulations Obstacle NLOS System Model NLOS ClassificationSea trial results 8

Sea Trial Description Obstacle NLOS System Model NLOS ClassificationSea trial results 9

Sea Trial Results Obstacle NLOS System Model NLOS ClassificationSea trial results 10 All Obstacle NLOS and LOS links were identified correctly

11 Summary NLOS identification problem If not detected, considerably affects localization accuracy Attenuation model Accurate models are hard to achieve. We rely only on lower bound on attenuation Distance estimations need not be accurate ToA vs. signal strength distance estimation Target strength and spreading loss lead to a noticeable difference between ToA and SS distance estimations Sea trial to validate performance Performed in a harbor environment with several Obstacle NLOS links All Obstacle NLOS and Loss links were identified Thresholding: compare both distance estimations

12 Reference list [1] W. Burdic, “Underwater Acoustic System Analysis,” Los Altos, CA, USA: Peninsula Publishing, 2002 [2] X. Cheng, H. Shu, Q. Liang, and D. Du, “Silent Positioning in Underwater Acoustic Sensor Networks,” IEEE Trans. Veh. Technol., vol. 57,no. 3, pp. 1756–1766, May [3] W. Cheng, A. Y. Teymorian, L. Ma, X. Cheng, X. Lu, and Z. Lu, “3D Underwater Sensor Network Localization,” IEEE Trans. on Mobile Computing, vol. 8, no. 12, pp. 1610–1621, December [4] L. Mu, G. Kuo, and N. Tao, “A novel ToA location algorithm using LOS range estimation for NLOS environments,” in Proc. of the IEEE Vehicular Technology Conference (VTC), Melbourne, Australia, May 2006, pp. 594–598. [5] S. Fischer, H. Grubeck, A. Kangas, H. Koorapaty, E. Larsson, and P. Lundqvist, “Time of arrival estimation of narrowband TDMA signal for mobile positioning,” Proc. of the IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), pp. 451–455, September [6] S. Woo, H. You, and J. Koh, “The NLOS mitigation technique for position loacation using IS-95 CDMA networks,” Proc. of the IEEE Vehicular Technology Conference (VTC), pp. 2556–2560, September [7] P. C. Chen, “A non-line-of-sight error mitigation algorithm in location estimation,” Proc. of the IEEE Wireless Communications and Networking Conference (WCNC), pp. 316–320, September [8] L. Cong and W. Zhuang, “Non-line-of-sight error mitigation in TDoA mobile location,” Proc. of the IEEE International Conference on Global Telecommunications (GlobeCom), vol. 1, pp. 680–684, November 2001

13 Thank you Questions?