2023_programme: Toward Practical Detection and Classification of Underwater Munitions with Electromagnetic Induction Sensing

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  • Session: 08. Munition Detection- Classification and Localization in the Marine Environment
    Organiser(s): David Bradley
  • Lecture: Toward Practical Detection and Classification of Underwater Munitions with Electromagnetic Induction Sensing
    Paper ID: 2064
    Author(s): Song LinPing, Billings Stephen, Pasion Leonard, Sinex David, Beran Laurens
    Presenter: Song LinPing
    Abstract: Increased human recreational and industrial activities in the offshore environment have led to more potential interactions with discarded military munitions (DMM) and Unexploded Ordnances (UXO). Electromagnetic induction (EMI) sensing has emerged as a promising technique for detection and characterization of metallic items in the complex marine environment. Marine EMI sensing, which is adopted from the terrestrial environment, aims to identify and classify potential UXO items based on the polarizabilities (an intrinsic physical property) of a target. \n\nMarine EMI sensing has some unique physical and operational challenges: (i) the EMI response of a target of interest can be significantly obscured or distorted by a strong, variable background response arising from the conductive seawater; (ii) Signal levels are reduced rapidly with increasing stand-off distance to the seafloor; and (iii) accurate estimates of sensor positions are difficult to achieve underwater, particularly when marine EMI surveys are collected in a dynamic, continuous acquisition mode. \n\nIn this presentation, we report on our efforts to address these technical difficulties with marine EMI surveys. Our developments include: (i) an integral equation-based characterization and modeling of responses of a multilayer marine environment; (ii) calibration of EMI measurements and effective background removal via the layered model; (iii) enhancement of target detectability by a synthetic aperture technique; and (iv) robust inversion of underwater EMI data by implementing algorithms that are tolerant of sensor positioning errors. These improved methods are integrated into a complete marine processing strategy. This processing strategy was assessed with UltraTEM Marine data acquired at the Sequim Bay test-site in Washington State. Calibration and Blind Grid results demonstrated that our approach was effective in accurately recovering principal axis polarizabilities of Targets of Interest (TOI) and in classifying items as either TOI or clutter.
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  • Corresponding author: Dr LinPing Song
    Affiliation: Black Tusk Geophysics Inc.
    Country: Canada
    e-mail:

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