iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://unpaywall.org/10.1007/S12083-018-0678-5
A three dimensional tracking scheme for underwater non-cooperative objects in mixed LOS and NLOS environment | Peer-to-Peer Networking and Applications Skip to main content
Log in

A three dimensional tracking scheme for underwater non-cooperative objects in mixed LOS and NLOS environment

  • Published:
Peer-to-Peer Networking and Applications Aims and scope Submit manuscript

Abstract

Underwater positioning and tracking scheme for non-cooperative objects is of great essence to explore unknown fields. Due to the high response time and non-line-of-sight(NLOS) propagation in the underwater acoustic sensor networks (UASNs), the existed range-based 3D target tracking algorithms are generally inaccurate on detecting underwater non-cooperative objects. In order to solve the problems above, the corresponding solutions are presented respectively in this paper. Although it is hard to change the inherent property of the underwater acoustic propagation, reducing the communication time is another way to solve the problem indirectly. Since the ranging phase and synchronize phase occupy most of the communication time, the presented novel ranging scheme for non-cooperative objects reduces the redundant time consumption, and further eliminates the necessity of synchronization process in advanced. For NLOS propagation, a distributed residual weighting discrimination (DRWD) algorithm based on grouping strategy is proposed for non-cooperative objects. The position estimations of the groups containing the NLOS link error are always distributed in isolation, and the estimations without the NLOS link errors are always concentrated in a small range. According to this feature, a low computational complexity approach namely two-step least square (LS) is proposed to determine the best location by analyzing the distribution of estimated coordinates. Meanwhile, a parameterized selection strategy is proposed first time to evaluate the construction of reference nodes in 3D target tracking. We provide a mathematical proof for our strategy, which avoids the ambiguity occurrence caused by the distribution of reference nodes. The new scheme provided for underwater acoustic tracking (UWAT) greatly improves the positioning accuracy in mixed LOS/NLOS environment. At the end of the paper, simulations are illustrated to evaluate and validate the algorithmic superiority and effectiveness.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  1. Heidemann J, Ye W, Wills J, Syed A, Li Y (2006) Research challenges and applications for underwater sensor networking. In: Wireless Communications and Networking Conference, 2006. WCNC 2006. IEEE, vol. 1, pp. 228–235 IEEE

  2. Chandrasekhar V, Seah WK, Choo YS, Ee HV (2006) Localization in underwater sensor networks:survey and challenges. In: IEEE Signal Processing and Communications Applications Conference, pp 33–40

  3. Liu Z, Wang S, Liu Y, Wang Y (2018) Secrecy transmission for femtocell networks against external eavesdropper. IEEE Trans Wirel Commun 99:1–1. https://doi.org/10.1109/TWC.2018.2836431

    Google Scholar 

  4. Erol-Kantarci M, Mouftah HT, Oktug S (2011) A survey of architectures and localization techniques for underwater acoustic sensor networks. IEEE Commun Surv Tutorials 13(3):487–502

    Article  Google Scholar 

  5. Liu Z, Wang J, Xia Y, Fan R, Jiang H, Yang H (2016) Power allocation robust to time-varying wireless channels in femtocell networks. IEEE Trans Veh Technol 65(4):2806–2815

    Article  Google Scholar 

  6. Rawat P, Singh KD, Chaouchi H, Bonnin JM (2014) Wireless sensor networks: a survey on recent developments and potential synergies. J Supercomput 68(1):1–48

    Article  Google Scholar 

  7. Chitre M, Shahabudeen S, Stojanovic M (2008) Underwater acoustic communications and networking: Recent advances and future challenges. Mar Technol Soc J 42(1):103–116

    Article  Google Scholar 

  8. Berger CR, Zhou S, Willett P, Liu L (2008) Stratification effect compensation for improved underwater acoustic ranging. IEEE Trans Signal Process 56(8):3779–3783

    Article  MathSciNet  MATH  Google Scholar 

  9. Ramezani H, Rad HJ, Leus G (2013) Target localization and tracking for an isogradient sound speed profile. IEEE Trans Signal Process 61(6):1434–1446

    Article  MathSciNet  MATH  Google Scholar 

  10. Patwari N, Ash JN, Kyperountas S, Hero AO, Moses RL, Correal NS (2005) Locating the nodes: cooperative localization in wireless sensor networks. IEEE Signal Process Mag 22(4):54–69

    Article  Google Scholar 

  11. Wang B, Zhou S, Liu W, Mo Y (2015) Indoor localization based on curve fitting and location search using received signal strength. IEEE Trans Ind Electron 62(1):572–582

    Article  Google Scholar 

  12. Wang G, So AM-C, Li Y (2016) Robust convex approximation methods for tdoa-based localization under nlos conditions. IEEE Trans Signal Process 64(13):3281–3296

    Article  MathSciNet  MATH  Google Scholar 

  13. Liu Z, Zheng Q, Xue L, Guan X (2012) A distributed energy-efficient clustering algorithm with improved coverage in wireless sensor networks. Futur Gener Comput Syst 28(5):780–790

    Article  Google Scholar 

  14. Vaghefi RM, Gholami MR, Buehrer RM, Strom EG (2013) Cooperative received signal strength-based sensor localization with unknown transmit powers. IEEE Trans Signal Process 61(6):1389–1403

    Article  MathSciNet  MATH  Google Scholar 

  15. Zhou Z, Peng Z, Cui J-H, Shi Z, Bagtzoglou A (2011) Scalable localization with mobility prediction for underwater sensor networks. IEEE Trans Mob Comput 10(3):335–348

    Article  Google Scholar 

  16. Braca P, Willett P, LePage KD, Marano S, Matta V (2014) Bayesian tracking in underwater wireless sensor networks with port-starboard ambiguity. IEEE Trans Signal Process 62(7):1864–1878

    Article  MathSciNet  MATH  Google Scholar 

  17. Stojanovic M (2007) On the relationship between capacity and distance in an underwater acoustic communication channel. ACM SIGMOBILE Mob Comput Commun Rev 11(4):34–43

    Article  Google Scholar 

  18. Domingo MC (2008) Overview of channel models for underwater wireless communication networks. Phys Commun 1(3):163–182

    Article  Google Scholar 

  19. Cho H-H, Chen C-Y, Shih TK, Chao H-C (2014) Survey on underwater delay/disruption tolerant wireless sensor network routing. IET Wireless Sens Syst 4(3):112–121

    Article  Google Scholar 

  20. Carroll P, Zhou S, Mahmood K, Zhou H, Xu X, Cui J-H (2012) On-demand asynchronous localization for underwater sensor networks. In: Oceans, 2012, pp 1–4 IEEE

  21. Cheng X, Shu H, Liang Q, Du DH-C (2008) Silent positioning in underwater acoustic sensor networks. IEEE Trans Veh Technol 57(3):1756–1766

    Article  Google Scholar 

  22. Diamant R, Tan H-P, Lampe L (2010) Nlos identification using a hybrid toa-signal strength algorithm for underwater acoustic localization. In: Oceans, 2010, pp. 1–7 IEEE

  23. Yu K, Guo YJ (2009) Statistical nlos identification based on aoa, toa, and signal strength. IEEE Trans Veh Technol 58(1):274–286

    Article  Google Scholar 

  24. Diamant R, Tan H-P, Lampe L (2014) Los and nlos classification for underwater acoustic localization. IEEE Trans Mob Comput 13(2):311–323

    Article  Google Scholar 

  25. Chen P-C (1999) A non-line-of-sight error mitigation algorithm in location estimation. In: Wireless Communications and Networking Conference, 1999. WCNC. 1999 IEEE, vol. 1, pp. 316–320 IEEE

  26. Hammes U, Zoubir AM (2010) Robust mobile terminal tracking in nlos environments based on data association. IEEE Trans Signal Process 58:5872–5882

    Article  MathSciNet  MATH  Google Scholar 

  27. Yin F, Fritsche C, Gustafsson F, Zoubir AM (2013) Toa-based robust wireless geolocation and cramér-rao lower bound analysis in harsh los/nlos environments. IEEE Trans Signal Process 61(9):2243–2255

    Article  Google Scholar 

  28. Huang Y, Liang W, Yu H-b, Xiao Y (2008) Target tracking based on a distributed particle filter in underwater sensor networks. Wirel Commun Mob Comput 8(8):1023–1033

    Article  Google Scholar 

  29. Liu Z, Gao H, Wang W, Chang S, Chen J (2015) Color filtering localization for three-dimensional underwater acoustic sensor networks. Sensors 15(3):6009–6032

    Article  Google Scholar 

  30. Tian C, Liu W, Jin J, Wang Y, Mo Y (2007) Localization and synchronization for 3d underwater acoustic sensor networks. Ubiquitous Intelligence Comput, pp 622–631

  31. Zhou Z, Cui J.-H., Zhou S (2007) Localization for large-scale underwater sensor networks, Networking 2007. Ad Hoc and Sensor Networks, Wireless Networks, Next Generation Internet, pp 108–119

  32. Isbitiren G, Akan OB (2011) Three-dimensional underwater target tracking with acoustic sensor networks. IEEE Trans Veh Technol 60(8):3897–3906

    Article  Google Scholar 

Download references

Acknowledgements

This work is partly supported by National Natural Science Foundation of China under grant 61473247, 61571387 and the Natural Science Foundation of Hebei Province under grant F2017203140 and F2017203084.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zhixin Liu.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of the Topical Collection: Special Issue on Big Data and Smart Computing in Network Systems

Guest Editors: Jiming Chen, Kaoru Ota, Lu Wang, and Jianping He

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yuan, Y., Li, Y., Liu, Z. et al. A three dimensional tracking scheme for underwater non-cooperative objects in mixed LOS and NLOS environment. Peer-to-Peer Netw. Appl. 12, 1369–1384 (2019). https://doi.org/10.1007/s12083-018-0678-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12083-018-0678-5

Keywords

Navigation