Joint time-frequency analysis is applied to radar imaging
problems. Special attention is given to imaging applications, for
which the resolution is severely limited due the available
bandwidth of the radar signal both in range and cross-range. This
includes the detection of landmines as well as foliage penetration
radar imaging. Motivated by this type of imaging problem a new
joint time-frequency method, the STPDFT algorithm is introduced
and compared with existing methods. The performance of all methods
is illustrated with synthetic test signals. In addition,
preliminary results are presented which demonstrate the
performance of joint-time frequency transforms, if applied to low
resolution imaging problems.
For weakly scattering permittivities, each measurement of the scattered far field can be interpreted as a sampling point of the Fourier transformation of the object. Furthermore, each sampling point can be accessed by more than one combination of wavelength, propagation direction, and polarization of the incident field. This means, a set of measurements which access the same sampling point can be regarded as being redundant. For strongly scattering objects the Fourier diffraction slice theorem does not apply. We show that measurements which are redundant in the weakly scattering case can be exploited to resolve difficulties associated with imaging of the strongly scattering objects. One dimensional geometries are investigated to estimate the potential redundant data sets offer for addressing the inverse scattering problem of strongly and multiply scattering objects. In addition, we discuss preliminary results for solving 2D imaging problems.