Despite ongoing research and development efforts, landmine and unexploded ordnance infestation continues to be a problem. Remediation efforts typically utilise inexpensive hand-held metal detectors that rely on the principle of electromagnetic induction. While these devices often detect all relevant metal objects, they generally cannot discriminate between harmful objects and harmless clutter. False indications continue to far outnumber verified detections. One promising method for improving the discrimination between harmful and harmless objects is the use of sensor arrays that provide images of hidden objects and complementary information about the buried object from a variety of angles. This paper will review the progress of high-resolution inductive and capacitive sensing array development for buried object detection. These sensor arrays use unique designs incorporating a single drive with multiple sense elements. The drive creates a shaped magnetic or electric field pattern that concentrates the field energy into longer wavelength spatial modes with 'focused' penetration into the ground. Images obtained from scans over buried objects provide a basis for spatial filtering and signal processing while multiple sensor arrays placed at different positions within the drive provide different 'views' of buried objects and clutter. Model-based grid measurement methods will also be reviewed as a real-time method for multiple property measurements, and real-time data analysis/image generation.


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    Titel :

    Inductive and capacitive array imaging of buried objects


    Weitere Titelangaben:

    Induktive und kapazitive Array-Abbildung von vergrabenen Objekten


    Beteiligte:
    Schlicker, D. (Autor:in) / Washabaugh, A. (Autor:in) / Shay, I. (Autor:in) / Goldfine, N. (Autor:in)

    Erschienen in:

    Insight ; 48 , 5 ; 302-306


    Erscheinungsdatum :

    2006


    Format / Umfang :

    5 Seiten, 10 Bilder, 7 Quellen




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch




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