A team of engineers and researchers is currently in the process of planning and conducting the largest ever survey at the Former Buckley Field in Colorado, by using SRI airborne ground penetrating SAR. The purpose of this survey is the detection of surface and subsurface Unexploded Ordnance (UXO) and in a broader sense the site characterization for identification of contaminated as well as clear areas. In preparation for such a large-scale survey, JPL has been developing advanced algorithms and a high-performance testbed for processing of massive amount of expected SAR data from this site. Two key requirements of this project are the accuracy and speed of SAR data processing. The first key feature of this testbed is a large degree of automation and maximum degree of the need for human perception in the processing to achieve an acceptable processing rate of several hundred acres per day. For accurate UXO detection, novel algorithms have been developed and implemented. These algorithms analyze dual polarized SAR data. They are based on the correlation of HH and VV SAR data and involve a rather large set of parameters for accurate detection of UXO. For each specific site, this set of parameters can be optimized by using ground truth data. In this paper, we discuss these algorithms and their successful application for detection of surface and subsurface anti-tank mines by using a data set from Yuma Proving Ground acquired by SRI SAR.


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    Title :

    Advanced algorithms and high performance testbed for large scale site characterization and subsurface target detection using airborne ground penetrating SAR


    Contributors:
    Fijany, A. (author) / Collier, J.B. (author) / Citak, A. (author)


    Publication date :

    1999


    Size :

    12 Seiten, 6 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English





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