We study the backscattered echoes from selected targets that are extracted by an impulse radar system playing the role of a ground penetrating radar (GPR). The targets are metal and nonmetal objects buried to a selected depth in dry sand in an indoor sandbox. The recorded time-series data are analyzed in the joint time-frequency domain using a pseudo-Wigner distribution (PWD). These distributions with their extracted features in the two-dimensional time-frequency domain are viewed as the target signatures. To be useful for target identification purposes, a signature representation should display a 'sufficient' amount of distinguishing features, yet be robust enough to suppress the interference of noise contained in the received signals. Multiple scattering between a target and the surface of the ground is another obstacle for successful target recognition that time-frequency distributions could counteract by unveiling the time progression of the returned target information. We have previously demonstrated the merits of the PWD relative to various competing time-frequency distributions, in particular its capability of extracting a target's time-frequency signature when the target is buried at different depths. We have also used a classification method developed from the fuzzy C-means clustering technique to reduce the number and kind of features in the PWD signature templates. This is accomplished by converting the PWD signature into a point cluster representation and then reducing the cluster to a (smaller) number of cluster centers. This classification method has been further developed by associating a weight with each point in the cluster representation. We put the classification algorithm to a test against validation data taken from an additional set of returned echoes. The same targets are used but they are buried at a different location in the sand. Class membership of a target is then decided using a simple metric. The results of our investigation serve to assess the possibility of identifying subsurface targets using a GPR.

Date Published: 18 September 1998
PDF: 9 pages
Proc. SPIE 3371, Automatic Target Recognition VIII, (18 September 1998); doi: 10.1117/12.323875

Published in SPIE Proceedings Vol. 3371:
Automatic Target Recognition VIII
Firooz A. Sadjadi, Editor(s)