Projection pursuit classification methods applied to multiband polarimetric SAR imagery

Results are presented for an experiment utilizing land calibration targets imaged by the NRL ultrawideband synthetic aperture radar (NUWSAR). Projection pursuit statistical analysis tools were applied to a set of simultaneous L- and X-band polarimetric images of dihedrals and trihedrals to determine optimal and minimal combinations of polarization and radar bands for identifying different scatterers. The normalized mutual information function (NMIF) was used as a quantitative optimization measure. It was calculated for a series of combinations of frequencies and polarizations, beginning with the maximum set of all six elements (HH, VV, and HV for each of X- and L-bands), then continuing with successive elimination of single elements, then pairs, and so on. In principle, this will produce 6! (or 720) of such combinations. To illustrate the principle, only a subset of element combinations were eliminated, and it became clear that the NMIF decreases rapidly as one goes beyond 2 members. Results presented suggest that a `spectral´ display of these NMIF results correlates with scale size and shape of targets, and that different types of targets in the scene display a robust NMIF spectral signature. This leads one to hypothesize that such an approach may lead to NMIF library signatures for classification of natural and man made targets similar to the way optical hyperspectral library signatures are utilized, but using microwave radar band and polarization combinations instead