Skip to main content
SpringerLink
Log in

Seismic modelling of tracked-vehicle signals for monitoring and verification

  • Disaster prediction
  • Published:
Applied Geophysics Aims and scope Submit manuscript

Abstract

To better understand characteristics of seismic signals of tracked vehicles measured when passing a sensor line, we numerically modelled force-pulse responses of a layered soil that is similar in its seismic properties to that found at the original measurement site. The vertical-force pulses from the road wheels rolling over the track elements are fitted to the measured ones. Single-pulse seismic waves vary with distance due to different wave types, reflections at layer boundaries, vehicle velocity and relative position of the left and right track elements. They are computed by a modelling program and superposed at sensor positions with the appropriate slant distance and time shift for each track element. These sum signals are in qualitative agreement with those from the original measurements. However, they are several magnitudes weaker and much smoother. Furthermore, higher frequencies are damped much less at larger distances. Due to the large variability of the sum signals, recognition of tracked-vehicle types exclusively through their seismic signals seems difficult.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Albert, D. G., 1987, The effect of snow on vehicle-generated seismic signatures: Journal of the Acoustical Society of America, 81(4), 881–887, Doi: https://doi.org/10.1121/1.394568.

    Article  Google Scholar 

  • Altmann, J., 2004, Acoustic and seismic signals of heavy military vehicles for co-operative verification: Journal of Sound and Vibration, 273(4–5), 713–740, Doi: https://doi.org/10.1016/j.jsv.2003.05.002.

    Article  Google Scholar 

  • Altmann, J., S. Linev and A. Weiß, 2002, Acoustic-seismic detection and classification of military vehicles—developing tools for disarmament and peace-keeping: Applied Acoustics, 63(10), 1085–1107, Doi: https://doi.org/10.1016/S0003-682X(02)00021-X.

    Article  Google Scholar 

  • Anderson, T. S., M. L. Moran, S. A. Ketcham, et al., 2004, Tracked Vehicle Simulations and Seismic Wavefield Synthesis in Seismic Sensor Systems: Computing in Science & Engineering, 6(6), 22–28, Doi:https://doi.org/10.1109/MCSE.2004.77.

    Article  Google Scholar 

  • Blanc, É., D. Komatitsch, E. Chaljub, et al., 2016, Highly accurate stability-preserving optimization of the Zener viscoelastic model, with application to wave propagation in the presence of strong attenuation: Geophysical Journal International, 205(1), 427–439, Doi: https://doi.org/10.1093/gji/ggw024.

    Article  Google Scholar 

  • csimsoft, 2017, Trelis Pro, http://www.csimsoft.com/trelis-pro (visited on 07/10/2017).

  • Duarte, M. F. and Y. H. Hu, 2004, Vehicle classification in distributed sensor networks: Journal of Parallel and Distributed Computing, 64(7), 826–838, Doi: https://doi.org/10.1016/j.jpdc.2004.03.020.

    Article  Google Scholar 

  • Foss, C. F., ed., 1987, Jane’s Armour and Artillery 1987–88. London, New York: Jane’s Publishing.

    Google Scholar 

  • Galaitsis, A. G. and W. B. Coney, 1999, Recent advances in the prediction of tracked vehicle seismic signatures: Proceedings of the 1999 Meeting of the IRIS Specialty Group on Acoustic and Seismic Sensing.

  • Ghosh, R., Akula, A., Kumar, S., et al., 2015, Time-frequency analysis based robust vehicle detection using seismic sensor: Journal of Sound and Vibration, 346, 424–434, Doi: https://doi.org/10.1016/j.jsv.2015.02.011.

    Article  Google Scholar 

  • Hunnicutt, R. P., 1999, Bradley: A History of American Fighting and Support Vehicles, Novato, CA: Presidio Press.

    Google Scholar 

  • IT & Medien Centrum der Technischen Universität Dortmund, 2018, LiDO, https://www.itmc.tu-dortmund.de/cms/de/dienste/hochleistungsrechnen/lido2/index.html (visited on 08/02/2018).

  • Ketcham, S. A., M. L. Moran, J. Lacombe, et al., 2005, Seismic source model for moving vehicles: IEEE Transactions on Geoscience and Remote Sensing, 43(2), 248–256, Doi: https://doi.org/10.1109/TGRS.2004.842212.

    Article  Google Scholar 

  • Komatitsch, D. and J. Tromp, 1999, Introduction to the spectral-element method for 3-D seismic wave propagation: Geophysical Journal International, 139(3), 806–822, Doi: https://doi.org/10.1046/j.1365-246x.1999.00967.x.

    Article  Google Scholar 

  • ——, 2002a, Spectral-element simulations of global seismic wave propagation-I. Validation: Geophysical Journal International, 149(2), 390–412, Doi: https://doi.org/10.1046/j.1365-246X.2002.01653.x.

    Article  Google Scholar 

  • ——, 2002b, Spectral-element simulations of global seismic wave propagation-II. Three-dimensional models, oceans, rotation nd self-gravitation: Geophysical Journal International, 150(1), 303–318.

    Article  Google Scholar 

  • Krylov, V. V., Pickup, S., and McNuff, J., 2010, Calculation of ground vibration spectra from heavy military vehicles: Journal of Sound and Vibration, 329(15), 3020–3029, Doi: https://doi.org/10.1016/j.jsv.2010.02.014.

    Article  Google Scholar 

  • Lacombe, J., Moran, M. L. and Harjes, D., 2001, Mechanical system simulations for seismic signature modeling: Proceedings of the 2001 Meeting of the Military Sensing Symposia (MSS), specialty group on battlefield acoustic and seismic sensing, Infrared Information Analysis Center, Veridian Systems Division.

  • Li, Dan, Wong, K. D., Hu, Y. H., et al., 2002, Detection, classification, and tracking of targets: IEEE Signal Processing Magazine, 19(2), 17–29, Doi: https://doi.org/10.1109/79.985674.

    Article  Google Scholar 

  • Pellegrini, F., 2017, Scotch & PT-Scotch — Software package and libraries for sequential and parallel graph partitioning, static mapping and clustering, sequential mesh and hypergraph partitioning, and sequential and parallel sparse matrix block ordering, https://www.labri.fr/perso/pelegrin/scotch/ (visited on 07/11/2017).

  • Peter, D., D. Komatitsch, Y. Luo, et al., 2011, Forward and adjoint simulations of seismic wave propagation on fully unstructured hexahedral meshes: Geophysical Journal International, 186(2), 721–739, Doi: https://doi.org/10.1111/j.1365-246X.2011.05044.x.

    Article  Google Scholar 

  • Rowland, D., 1972, Tracked vehicle ground pressure and its effect on soft ground performance: Proceedings of the 4th International Conference of the International Society for Terrain-Vehicle Systems, 1, Stockholm, Sweden.

  • Scheibert, M., 1983, Kampfpanzer LEOPARD 1 mit neuen Dimensionen im Panzerbau, Dorheim: Podzun-Pallas-Verlag.

    Google Scholar 

  • Scholl, James F., L. P. Clare and J. R. Agre, 1999, Seismic Attenuation Characterization using Tracked Vehicles, Ft. Belvoir VA: Department of the Army, https://apps.dtic.mil/dtic/tr/fulltext/u2/a410999.pdf (visited on 06/08/2020).

    Google Scholar 

  • Schön, J. H., 2011, Physical Properties of Rocks: A Workbook, Handbook of Petroleum Exploration and Production 8, Amsterdam, Oxford, Waltham MA: Elsevier.

    Google Scholar 

  • ——, 2015, Physical Properties of Rocks: Fundamentals and Principles of Petrophysics. 2nd ed. Developments in Petroleum Science Volume 65, Second Edition: Fundamentals and Principles of Petrophysics. Amsterdam, Oxford, Waltham MA: Elsevier.

  • Tonn, R., 1991, The determination of the seismic quality factor Q from VSP data: A comparison of different computational methods: Geophysical Prospecting, 39(1), 1–27, doi: https://doi.org/10.1111/j.1365-2478.1991.tb00298.x.

    Article  Google Scholar 

  • Tromp, J., Komatitsch, D., and Liu, Q., 2008, Spectral-Element and Adjoint Methods in Seismology: Communications in Computational Physics, 3(1), 1–32.

    Google Scholar 

  • William, P. E., and Hoffman, M. W., 2011, Classification of Military Ground Vehicles Using Time Domain Harmonics’ Amplitudes: IEEE Transactions on Instrumentation and Measurement, 60, 3720–3731.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Experimentelle Physk III, TU Dortmund University, 44221, Dortmund, Germany

    Mathias Pilch & Jürgen Altmann

Authors
  1. Mathias Pilch
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jürgen Altmann
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mathias Pilch.

Additional information

Mathias Pilch has earned a B.Sc. in Physics in 2015 at TU Dortmund University, Germany, with work on computer simulations on the fitness of species developing under different theories on evolution. In January 2018 he has finished his M.Sc. thesis about numerical modelling of seismic tracked-vehicle signals for co-operative verification.

Jürgen Altmann, PhD, is a physicist and peace researcher at TU Dortmund University, Germany. Since 1985 he has studied scientific-technical problems of disarmament. An experimental focus is automatic sensor systems for cooperative verification of disarmament and peace agreements and for IAEA safeguards for an underground final repository. Another focus is assessment of new military technologies and preventive arms control.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pilch, M., Altmann, J. Seismic modelling of tracked-vehicle signals for monitoring and verification. Appl. Geophys. 18, 253–264 (2021). https://doi.org/10.1007/s11770-021-0898-y

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11770-021-0898-y

Keywords

Search

Navigation