FINITE-DIFFERENCE TIME-DOMAIN FORMULATION OF AN INVERSE SCATTERING SCHEME FOR REMOTE-SENSING OF CONDUCTING AND DIELECTRIC TARGETS .2. 2-DIMENSIONAL CASE
M. Strickel et al., FINITE-DIFFERENCE TIME-DOMAIN FORMULATION OF AN INVERSE SCATTERING SCHEME FOR REMOTE-SENSING OF CONDUCTING AND DIELECTRIC TARGETS .2. 2-DIMENSIONAL CASE, Journal of electromagnetic waves and applications, 8(4), 1994, pp. 509-529
This paper introduces a technique for time-domain electromagnetic inve
rse scattering based upon the use of a two-dimensional, finite-differe
nce time-domain (FD-TD) forward scattering field representation in num
erical feedback loop with a nonlinear optimization routine. Causality
is exploited to reconstruct the actual target surface contour in a seq
uential and cumulative manner as the illuminating wavefront sweeps acr
oss the target. This approach appears to require a minimum amount of s
cattered field information. A number of examples are reported where th
e only data needed is the time waveform of a scattered pulse for the t
ransverse magnetic (TM) polarization case, observed at just a single p
oint in the near field. These examples include the reconstruction of t
wo-dimensional conducting and homogeneous dielectric target shapes suc
h as triangles, rectangles, and trapezoids. A dielectric target with r
eentrant features, resembling the letter ''J'' is also reconstructed f
rom a single point observation. The effects of measurement signal-to-n
oise ratio upon this inverse-scattering technique are determined via n
umerical experiments. These effects are discussed in two contexts: 1)
probability of exact reconstruction vs. signal-to-noise ratio, and 2)
sensitivity of reconstructions to noise. It is shown that, even at low
signal-to-noise ratios (where the probability of exact reconstruction
is also low), the imperfectly-reconstructed targets retain many of th
e distinguishing features of the original target. This indicates that
the reconstruction process is quite robust relative to noise. Developm
ents in nonlinear optimization appear promising for further improving
the reliability and quality of target reconstruction in noise.