Method for Minefields Mapping by Imagery from Unmanned Aerial Vehicle

Authors

  • M.O. Popov Scientific Centre for Aerospace Research of the National Academy of Sciences of Ukraine, Kyiv, Ukraine
  • S.A. Stankevich Scientific Centre for Aerospace Research of the National Academy of Sciences of Ukraine, Kyiv, Ukraine
  • S.P. Mosov Institute of Public Administration and Research in Civil Protection, SES of Ukraine, Kyiv, Ukraine
  • O.V. Titarenko Scientific Centre for Aerospace Research of the National Academy of Sciences of Ukraine, Kyiv, Ukraine
  • S.S. Dugin Scientific Centre for Aerospace Research of the National Academy of Sciences of Ukraine, Kyiv, Ukraine
  • S.I. Golubov Scientific Centre for Aerospace Research of the National Academy of Sciences of Ukraine, Kyiv, Ukraine
  • A.A. Andreiev Scientific Centre for Aerospace Research of the National Academy of Sciences of Ukraine, Kyiv, Ukraine

DOI:

https://doi.org/10.3849/aimt.01722

Keywords:

landmine detection, minefield mapping, multispectral camera, probability fusion, thermal infrared camera, uncertainty level, unmanned aerial vehicle

Abstract

The paper proposes a method for minefields mapping by the centimeter resolution imagery from a copter-type unmanned aerial vehicle (UAV) which is equipped with multispectral camera and thermal infrared camera. The research methodology is the probability fusion by each sensor and the subsequent decision making on the landmine presence/absence. Models for the landmine detection in multispectral and thermal images are considered. The training sample structuration is proposed for the landmine detection reliability enhancement. The local temperature anomalies of landmine size are allocated by sliding window scanning the thermal image. The experimental performance of actual landmines detection at a special test site in Ukraine is described. The probability of correct landmine detection was 0.92 while with a false alarm probability it was 0.45.

 

Author Biography

  • M.O. Popov, Scientific Centre for Aerospace Research of the National Academy of Sciences of Ukraine, Kyiv, Ukraine

    Director

References

BALL, M. Landmine Detection with Drones. Unmanned Systems Technology [online], 2021 [viewed 2022-05-17] Available from: https://www.unmannedsystemstechnology.com/2021/08/landmine-detection-with-drones/

Detectors and Personal Protective Equipment Catalogue [online]. Geneva: GICHD, 2009 [viewed 2022-05-17]. ISBN 978-2-940369-23-2. Available from: https://www.files.ethz.ch/isn/97269/Metal-Detectors-Catalogue-2009.pdf

EGE, Y., A. KAKILLI, O. KILIÇ, H. ÇALIK, H. ÇITAK, S. NAZLIBILEK and O. KALENDER. Performance Analysis of Techniques Used for Determining Land Mines. International Journal of Geosciences, 2014, 5(10), pp. 1163-1189. https://doi.org/10.4236/ijg.2014.510098.

MAATHUIS, B.H.P. Remote Sensing Based Detection of Minefields. Geocarto International, 2003, 18(1), pp. 51-60. https://doi.org/10.1080/10106040308542263.

Acronyms and Slang [online], 2022. [viewed 2022-05-17] Available from: http://acronymsandslang.com/definition/5267718/AMDAS-meaning.html

GAUR, P. and T. CHOUDHARY. Aerial Landmine Detection. International Journal of Engineering & Technology, 2018, 7(3.34), pp. 710-713. https://doi.org/10.14419/ijet.v7i3.34.19457.

FARDOULIS, J., X. DEPREYTERE, P. GALLIEN, K. DJOUHRI, B. ABDOURHMANE and E. SAUVAGE. Proof: How Small Drones Can Find Buried Landmines in the Desert Using Airborne IR Thermography. Journal of Conventional Weapons Destruction, 2020, 24(2), pp. 55-63. https://doi.org/10.5281/zenodo.4409641.

RAJ, A., I. RAFIQ, A.J. GOWDA and L.S. KRISHNA. Landmines Detection Using UAV. International Research Journal of Engineering and Technology [online], 2019, 6(4), pp. 2716-2719 [viewed 2022-05-17]. Available from: https://www.irjet.net/archives/V6/i4/IRJET-V6I4577.pdf

CASTIBLANCO, C., J. RODRIGUEZ, I. MONDRAGON, C. PARRA and J. COLORADO. Air Drones for Explosive Landmines Detection. In: ARMADA, M., A. SANFELIU and M. FERRE, eds. ROBOT2013: First Iberian Robotics Conference. Advances in Intelligent Systems and Computing. Cham: Springer, 2014, pp. 107-114. ISBN 978-3-319-03652-6.

COLOMINA, I. and P. MOLINA. Unmanned Aerial Systems for Photogrammetry and Remote Sensing: A Review. ISPRS Journal of Photogrammetry and Remote Sensing, 2014, 92, pp. 79-97. https://doi.org/10.1016/j.isprsjprs.2014.02.013.

RACEK, F., T. BALÁŽ T. and P. MELŠA. Hyperspectral Data Conversion in the Case of Military Surveillance. Advances in Military Technology [online], 2015, 10(1), pp. 5-13. [viewed 2022-05-17]. Available from: https://aimt.cz/index.php/aimt/article/1054

XIANG, T.-Z., G.-S. XIA and L. ZHANG. Mini-Unmanned Aerial Vehicle-Based Remote Sensing: Techniques, Applications, and Prospects. IEEE Geoscience and Remote Sensing Magazine, 2019, 7(3), pp. 29-63. https://doi.org/10.1109/MGRS.2019.2918840.

POPOV, M.O., S.A. STANKEVICH, S.P. MOSOV, O.V. TITARENKO, M.V. TOPOLNYTSKYI and S.S. DUGIN. Landmine Detection with UAV-Based Optical Data Fusion. In: IEEE EUROCON 2021 - 19th International Conference on Smart Technologies. Lviv: IEEE, 2021, pp. 175-178. https://doi.org/10.1109/EUROCON52738.2021. 9535553.

LACROIX, V., Y. YVINEC and M. ACHEROY. Research at RMA in the Evolving Context of Mine Action. In: BEUMIER, C., D. CLOSSON, V. LACROIX, N. MILISAVLJEVIC and Y. YVINEC. Mine Action – The Research Experience of the Royal Military Academy of Belgium. London: IntechOpen, 2017, pp. 1-19. ISBN 978-953-51-3304-9.

LILLESAND, T.M., R.W. KIEFER and J.W. CHIPMAN. Remote Sensing and Image Interpretation. Hoboken: Wiley, 2015. ISBN 978-1-118-34328-9.

VENTURA, D., A. BONIFAZI, M.F. GRAVINA, A. BELLUSCIO and G. ARDIZZONE. Mapping and Classification of Ecologically Sensitive Marine Habitats Using Unmanned Aerial Vehicle (UAV) Imagery and Object-Based Image Analysis (OBIA). Remote Sensing, 2018, 10(9), 1331. https://doi.org/10.3390/rs10091331.

BUDIHARTO, W., E. IRWANSYAH, J.S. SUROSO, A. CHOWANDA, H. NGARIANTO and A.A.S. GUNAWAN. Mapping and 3D Modelling Using Quadrotor Drone and GIS Software. Journal of Big Data, 2021, 8, 48. https://doi.org/10.1186/s40537-021-00436-8.

HOSMER Jr., D.W., S. LEMESHOW and R.X. STURDIVANT. Applied Logistic Regression. Hoboken: Wiley, 2013. ISBN 978-1-118-54838-8.

HILBE, J.M. Practical Guide to Logistic Regression. Boca Raton: CRC Press, 2015. ISBN 978-1-4987-0957-5.

KLEINBAUM, D.G. and M. KLEIN. Logistic Regression: A Self-Learning Text. New York: Springer, 2010. ISBN 978-1-4419-1741-1.

SINAGA, K.P. and M. YANG. Unsupervised k-Means Clustering Algorithm. IEEE Access, 2020, 8, pp. 80716-80727. https://doi.org/10.1109/ACCESS.2020.2988796.

STAROVOITOV, V.V. and Yu.I. GOLUB. Comparative Study of Quality Estimation of Binary Classification (in Russian). Informatics, 2020, 17(1), pp. 87-101. https://doi.org/10.37661/1816-0301-2020-17-1-87-101.

DAS, S.K. and R.S. SINGH. Performance Modelling of Electro-Optical Devices for Military Target Acquisition. Defence Science Journal, 2007, 57(3), pp. 323-331. https://doi.org/10.14429/dsj.57.1778.

TRUKHACHEV, A.A. Analysis of Procedures and Algorithms for Signal Detection (in Russian). Moscow: Radio & Communications, 2003.

HICKMAN, D.L. Target Detection: The Transition from Unresolved to Extended Targets. In: Proceedings of the SPIE, 2021, 11866. https://doi.org/10.1117/12.2597227.

CREMER, F., K. SCHUTTE, J.G.M. SCHAVEMAKER and E. DEN BREEJEN. A Comparison of Decision-Level Sensor-Fusion Methods for Anti-Personnel Landmine Detection. Information Fusion, 2001, 2(3), pp. 187-208. https://doi.org/10.1016/S1566-2535(01)00034-3.

DEN BREEJEN, E., K. SCHUTTE, and F. CREMER. Sensor Fusion for Anti-Personnel Landmine Detection: A Case Study. In: Proceedings of Detection and Remediation Technologies for Mines and Minelike Targets IV. Orlando: SPIE, 1999, 3710, pp. 1235-1245. https://doi.org/10.1117/12.357003.

KRTALIĆ, A., A.K. DIVJAK and R. ŽUPAN. Visualization of Land Mine Danger, Svilaja Region (Croatia). Journal of Maps, 2019, 15(1), pp. 21-29. https://doi.org/10.1080/17445647.2018.1552209.

KRTALIĆ, A. Thematic Maps for Humanitarian Demining. Kartografija i Geoinformacije [online], 2012, 11(17), pp. 26-41. [viewed 2022-05-17] Available from: https://kig.kartografija.hr/kig/article/view/41

SHAKHATREH, H., A.H. SAWALMEH, A. AL-FUQAHA, Z. DOU, E. ALMAITA, I. KHALIL, N.S. OTHMAN, A. KHREISHAH and M. GUIZANI. Unmanned Aerial Vehicles (UAVs): A Survey on Civil Applications and Key Research Challenges. IEEE Access, 2019, 7, pp. 48572-48634. https://doi.org/10.1109/ACCESS.2019.2909530.

PEPE, M., L. FREGONESE and M. SCAIONI. Planning Airborne Photogrammetry and Remote-Sensing Missions with Modern Platforms and Sensors. European Journal of Remote Sensing, 2018, 51(1), pp. 412-436. https://doi.org/10.1080/22797254.2018.1444945.

STANKEVICH, S.A., S.P. MOSOV and V.O. VOROVICH. Systematization of Conditions and Factors Influencing the Use of Drones in the Detection of Landmines (in Ukrainian). Collection of the Scientific Papers of the Centre for Military and Strategic Studies of the National Defence University of Ukraine named after Ivan Cherniakhovskyi [online], 2021, 3(73), pp. 82-89. https://doi.org/10.33099/2304-2745/2021-3-73/82-89. [viewed 2022-05-17]. Available from: http://znp-cvsd.nuou.org.ua/article/view/255344/252428.

MARQUES, L., G. MUSCATO, Y. YVINEC, M. PEICH, G. ALLI and G.A. TURNBULL. Sensors for Close-In Detection of Explosive Devices in the Framework of FP7-TIRAMISU Project. In: The EOD Future in the Light of NATO EOD Demonstrations and Trials 2012. Trenčín: NATO Centre of Excellence for Explosive Ordnance Disposal, 2013, pp. 63-74. ISBN 978-80-89261-42-0.

KRUIJFF, M., D. ERIKSSON, T. BOUVET, A. GRIFFITHS, M. CRAIG, H. SAHLI, F.V. GONZÁLEZ-ROSÓN, P. WILLEKENS and A. GINATI. Space Assets for Demining Assistance. Acta Astronautica, 2013, 83, pp. 239-259. https://doi.org/10.1016/j.actaastro.2012.08.016.

ZYADA, Z., Y. KAWAI, S. SATO, T. MATSUNO, Y. HASEGAWA and T. FUKUDA. GPR Environmental-Based Landmine Automatic Detection. In: HABIB M.K., ed. Humanitarian Demining. Vienna: IntechOpen, 2008, pp. 151-174. https://doi.org/10.5772/5412.

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Published

07-09-2022

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Research Paper

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How to Cite

Popov, M., Stankevich, S., Mosov, S., Titarenko, O., Dugin, S., Golubov, S., & Andreiev, A. (2022). Method for Minefields Mapping by Imagery from Unmanned Aerial Vehicle. Advances in Military Technology, 17(2), 211-229. https://doi.org/10.3849/aimt.01722

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