Abstract
In this paper, we discuss a modified Prony's algorithm for use in buried land mine detection from ground penetrating radar (GPR) data. The algorithm finds the dominant complex natural resonances (CNRs) for vectors of time-domain GPR data. We consider the identification of objects present in two-dimensional images. The CNR features of an unknown image are processed through distance-based detectors with the CNR features of known objects from an object library. We analyze our algorithm performance versus SNR and also analyze performance for different distance detectors.
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