Please provide your name and email to download


    First Name

    Last Name



    [wpv-post-taxonomy type="ctype" separator=", " format="link" show="name" order="asc"]
    UXO Classification Using Characteristic Modes of the Broadband Electromagnetic Induction Response

    Publisher –
    Zonge, 1999, 2000.  Variations of this paper have been presented at the following conferences:
    1. A New Technology Applications Conference on the Science and Technology of
    Unexploded Ordnance (UXO) Removal and site Remediation. Maui, Hawaii, November 8-11, 1999.
    2. SAGEEP 2000, Arlington, Virginia, February 20-24, 2000 (Proceedings, p. 747)
    3. Pacific Environmental Restoration Conference, Honolulu, Hawaii, April 4-7, 2000

    Authors –
    D.D. Snyder, Scott MacInnes*, Scott Urquhart*, and K.L. Zonge, Zonge Engineering and Research Organization, Inc., Tucson, Arizona USA

    Paper – [pdf]  UXO_Perc2000

    Electromagnetic induction methods are effective in locating unexploded ordnance (UXO). However, the induction EM instruments that are used for UXO detection generally have limited bandwidths and provide little, if any, information for UXO classification. It is well known that the broadband induction EM response from confined conductors (such as UXO) can be parameterized in the time-domain as a series of damped exponential decay curves, and in the frequency domain as a set of discrete real first order poles and their residues. Characteristic decay time or its equivalent real pole has been shown to be a function of characteristic target dimensions, target conductivity, and relative magnetic permeability. 
    Therefore, parameterization of the broadband EM response in terms of these characteristic modes provides a basis for the classification of UXO anomalies.

    In this paper we have used a numerical method (Prony) to analyze TEM decay curves to obtain a set of exponential decay time-constants and their corresponding residues. Using a commercially available field data acquisition system, we have acquired fast transient TEM data from UXO. We show that these data can be analyzed and displayed in a way that is simple to understand and useful for classifying the TEM response.