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By : Roee Diamant, Hwee-Pink Tan and Lutz Lampe

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. *. 1. Outline.

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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 * 1

  2. 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 3

  4. System Model System Model and Assumptions Obstacle NLOS NLOS Classification Sea trial results 4

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

  6. System Model NLOS Classification Obstacle NLOS NLOS Classification Sea trial results 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. 6

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

  8. System Model Simulations Obstacle NLOS NLOS Classification Sea trial results 8

  9. System Model Sea Trial Description Obstacle NLOS NLOS Classification Sea trial results 9

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

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

  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 2008. • [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 2009. • [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 1998. • [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 2000. • [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 1999. • [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 12

  13. Thank you Questions? 13

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