skip to main content
10.1145/3468691.3468703acmotherconferencesArticle/Chapter ViewAbstractPublication PagescniotConference Proceedingsconference-collections
research-article

A Wildlife Tracking Scheme in Forest Area Based on UAV and Sensors

Published:07 August 2021Publication History

ABSTRACT

In this paper, we aim to propose a wildlife tracking scheme for forest areas similar to the greater Khingan mountains in China. The classic outdoor positioning technology, such as global navigation satellite system (GNSS), has the advantages of all-weather positioning, global coverage and high positioning accuracy. However, due to more signal occlusion in forest areas, the GNSS positioning effect is not good. Another example is inertial navigation system (INS), which does not rely on external information or limited positioning environment, and has high positioning accuracy. However, as the positioning time increases, the positioning error of INS gradually accumulates, resulting in poor positioning effect. In this paper, we propose an animal tracking scheme based on Time difference of arrival (TDOA) localization algorithm and extended Kalman filter (EKF) with the help of Unmanned aerial vehicle (UAV) and Wireless sensor network (WSN) to solve the problem of wildlife monitoring in forest areas. The simulation results show that our scheme is feasible.

References

  1. A. G. Dempster and E. Cetin, "Interference Localization for Satellite Navigation Systems," in Proceedings of the IEEE, vol. 104, no. 6, pp. 1318-1326, June 2016, doi: 10.1109/JPROC.2016.2530814.Google ScholarGoogle ScholarCross RefCross Ref
  2. D. A. Grejner-Brzezinska, C. K. Toth, T. Moore, J. F. Raquet, M. M. Miller and A. Kealy, "Multisensor Navigation Systems: A Remedy for GNSS Vulnerabilities?," in Proceedings of the IEEE, vol. 104, no. 6, pp. 1339-1353, June 2016, doi: 10.1109/JPROC.2016.2528538.Google ScholarGoogle ScholarCross RefCross Ref
  3. G. Han, J. Jiang, C. Zhang, T. Q. Duong, M. Guizani and G. K. Karagiannidis, "A Survey on Mobile Anchor Node Assisted Localization in Wireless Sensor Networks," in IEEE Communications Surveys & Tutorials, vol. 18, no. 3, pp. 2220-2243, thirdquarter 2016, doi: 10.1109/COMST.2016.2544751.Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. A. Yassin , "Recent Advances in Indoor Localization: A Survey on Theoretical Approaches and Applications," in IEEE Communications Surveys & Tutorials, vol. 19, no. 2, pp. 1327-1346, Secondquarter 2017, doi: 10.1109/COMST.2016.2632427.Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. N. Zhu, J. Marais, D. Bétaille and M. Berbineau, "GNSS Position Integrity in Urban Environments: A Review of Literature," in IEEE Transactions on Intelligent Transportation Systems, vol. 19, no. 9, pp. 2762-2778, Sept. 2018, doi: 10.1109/TITS.2017.2766768.Google ScholarGoogle ScholarCross RefCross Ref
  6. K. Chen, G. Tan and M. Lu, "Improving the energy performance of GPS receivers for location tracking applications," 2017 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), Atlanta, GA, 2017, pp. 85-90, doi: 10.1109/INFCOMW.2017.8116357.Google ScholarGoogle Scholar
  7. P. Srinivas and A. Kumar, "Overview of architecture for GPS-INS integration," 2017 Recent Developments in Control, Automation & Power Engineering (RDCAPE), Noida, 2017, pp. 433-438, doi: 10.1109/RDCAPE.2017.8358310.Google ScholarGoogle Scholar
  8. Q. Xu, X. Li and C. Chan, "Enhancing Localization Accuracy of MEMS-INS/GPS/In-Vehicle Sensors Integration During GPS Outages," in IEEE Transactions on Instrumentation and Measurement, vol. 67, no. 8, pp. 1966-1978, Aug. 2018, doi: 10.1109/TIM.2018.2805231.Google ScholarGoogle ScholarCross RefCross Ref
  9. Y. Zhang, C. Shen, J. Tang and J. Liu, "Hybrid Algorithm Based on MDF-CKF and RF for GPS/INS System During GPS Outages (April 2018)," in IEEE Access, vol. 6, pp. 35343-35354, 2018, doi: 10.1109/ACCESS.2018.2849217.Google ScholarGoogle ScholarCross RefCross Ref
  10. J. N. Gross, Y. Gu and M. B. Rhudy, "Robust UAV Relative Navigation With DGPS, INS, and Peer-to-Peer Radio Ranging," in IEEE Transactions on Automation Science and Engineering, vol. 12, no. 3, pp. 935-944, July 2015, doi: 10.1109/TASE.2014.2383357.Google ScholarGoogle ScholarCross RefCross Ref
  11. G. Han, J. Jiang, C. Zhang, T. Q. Duong, M. Guizani and G. K. Karagiannidis, "A Survey on Mobile Anchor Node Assisted Localization in Wireless Sensor Networks," in IEEE Communications Surveys & Tutorials, vol. 18, no. 3, pp. 2220-2243, thirdquarter 2016, doi: 10.1109/COMST.2016.2544751.Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. F. Zafari, A. Gkelias and K. K. Leung, "A Survey of Indoor Localization Systems and Technologies," in IEEE Communications Surveys & Tutorials, vol. 21, no. 3, pp. 2568-2599, thirdquarter 2019, doi: 10.1109/COMST.2019.2911558.Google ScholarGoogle ScholarCross RefCross Ref
  13. J. Tiemann and C. Wietfeld, "Scalable and precise multi-UAV indoor navigation using TDOA-based UWB localization," 2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Sapporo, 2017, pp. 1-7, doi: 10.1109/IPIN.2017.8115937.Google ScholarGoogle Scholar
  14. C. R. Karanam, B. Korany and Y. Mostofi, "Magnitude-Based Angle-of-Arrival Estimation, Localization, and Target Tracking," 2018 17th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN), Porto, 2018, pp. 254-265, doi: 10.1109/IPSN.2018.00053.Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Z. Chen, L. Wang and L. Chen, "Virtual Antenna Array and Multipath AOA-Delay Fingerprints Based Location for Moving Targets," in IEEE Access, vol. 8, pp. 186919-186931, 2020, doi: 10.1109/ACCESS.2020.3029629.Google ScholarGoogle ScholarCross RefCross Ref
  16. G. Fokin, "AOA Measurement Processing for Positioning using Unmanned Aerial Vehicles," 2019 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom), Sochi, Russia, 2019, pp. 1-3, doi: 10.1109/BlackSeaCom.2019.8812834.Google ScholarGoogle Scholar
  17. Y. Wen, X. Tian, X. Wang and S. Lu, "Fundamental limits of RSS fingerprinting based indoor localization," 2015 IEEE Conference on Computer Communications (INFOCOM), Kowloon, 2015, pp. 2479-2487, doi: 10.1109/INFOCOM.2015.7218637.Google ScholarGoogle Scholar
  18. Z. Xiao, H. Wen, A. Markham, N. Trigoni, P. Blunsom and J. Frolik, "Non-Line-of-Sight Identification and Mitigation Using Received Signal Strength," in IEEE Transactions on Wireless Communications, vol. 14, no. 3, pp. 1689-1702, March 2015, doi: 10.1109/TWC.2014.2372341.Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. S. Tomic, M. Beko and R. Dinis, "3-D Target Localization in Wireless Sensor Networks Using RSS and AoA Measurements," in IEEE Transactions on Vehicular Technology, vol. 66, no. 4, pp. 3197-3210, April 2017, doi: 10.1109/TVT.2016.2589923.Google ScholarGoogle ScholarCross RefCross Ref
  20. L. Zhou and S. Ma, "Improved Hybrid Localization Algorithm of Maximum Likelihood and Centroid Localization Based on RSSI," 2017 4th International Conference on Information Science and Control Engineering (ICISCE), Changsha, 2017, pp. 385-389, doi: 10.1109/ICISCE.2017.87.Google ScholarGoogle Scholar
  21. Y. W. E. Chan and B. Soong, "Discrete Weighted Centroid Localization (dWCL): Performance Analysis and Optimization," in IEEE Access, vol. 4, pp. 6283-6294, 2016, doi: 10.1109/ACCESS.2016.2612225Google ScholarGoogle ScholarCross RefCross Ref
  22. Y. W. E. Chan and B. Soong, "Discrete Weighted Centroid Localization (dWCL): Performance Analysis and Optimization," in IEEE Access, vol. 4, pp. 6283-6294, 2016, doi: 10.1109/ACCESS.2016.2612225Google ScholarGoogle ScholarCross RefCross Ref

Recommendations

Comments

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Sign in
  • Published in

    cover image ACM Other conferences
    CNIOT '21: Proceedings of the 2021 2nd International Conference on Computing, Networks and Internet of Things
    May 2021
    270 pages
    ISBN:9781450389693
    DOI:10.1145/3468691

    Copyright © 2021 ACM

    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 7 August 2021

    Permissions

    Request permissions about this article.

    Request Permissions

    Check for updates

    Qualifiers

    • research-article
    • Research
    • Refereed limited

    Acceptance Rates

    Overall Acceptance Rate39of82submissions,48%
  • Article Metrics

    • Downloads (Last 12 months)25
    • Downloads (Last 6 weeks)1

    Other Metrics

PDF Format

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format .

View HTML Format