Department of Computer Science and Electrical Engineering
Land Mine Identification Using Microwave Resonance Signatures
David Kinnon
Abstract:
It has been proposed that plastic land mines can be identified based
on their physical properties using Ground Penetrating Radar (GPR). GPR
distinguishes landmines from extraneous subterranean clutter by virtue
of their dielectric constant. Classification patterns can be formulated
by identifying the Complex Resonance Signatures (CNRs) of the targets.
CNRs are comprised of the real and complex parts of the respective resonance
frequencies.
The backscattering from targets of particular length-to-diameter
ratio will resonate at specific frequencies. This resonance is unique to
that particular length-to-diameter ratio. The larger the length-to-diameter
ratio, the larger the exhibition of resonance. Hence long-thin targets
can be more easily identified that circular targets such as land mines.
Experiments involving thin copper wires of lengths 13, 14 and 15cm
were conducted using a Network Analyser - anechoic chamber set-up. The
wires were oriented parallel to the polarisation of the antennas. It was
observed that the backscattering contained complex resonances at wavelengths
that could be factored, using integer multiplication, into the length of
the wires.
The wires were then tested with azimuths of 45 degrees and 90 degrees
and elevations of 0 degrees and 45 degrees to test the polarisation and
orientation independence of CNRs respectively. It was observed that the
resonance frequencies remained constant as expected. The magnitudes of
the complex resonances (residues) decreased.
Auto-regressive spectral estimation techniques, based on the original
and least squares Prony algorithms, were applied to the transient response
of the backscatter to determine the CNRs. It was observed that the least
squares technique provided a very high degree of accuracy. The original
Prony algorithm proved fallible in the presence of noise.
Experiments involving surrogate land mines were conducted. Analysis
showed no evidence of CNRs. The feasibility of plastic and mine detection
and classification using CNRs, based on the results published in this dissertation,
is thus questionable. However, CNRs of unexploded ordnance is worthy of
further investigation.
Complete thesis:
thesis.pdf
Additional material:
conference.PDF
About the Author