This paper contains the first step in an overall approach to low- frequency SAR target detection and classification through direct exploitation of signature physics. The SAR imaging algorithm has been modified to take some of the available signature information into account. More specifically, a simple detection filter is constructed to approximately match the dominant dihedral response from a side of a man-made vehicle, which is not dominant in tree responses. The matching takes place along the image formation integration path in raw dwell data that produces a single image pixel. This integration path measures response versus viewing angle. Since target orientation is unknown, a filter bank is used. Although the dihedral RCS is also matched in frequency, the primary filter gain comes from matching the limited azimuthal response of the dihedral. Further gain may be provided by polarization diversity, but this is unknown since the radar under study measures only HH polarization. In a detection performance comparison with conventional image formation and processing techniques, the current matched filter image formation technique appears to be the only one offering significant improvement. Since the technique is fundamentally limited by the ability to view a vehicle side, it is recommended to increase the radar azimuthal beamwidth to ninety degrees or more. Our overall concept to detection and classification uses a multistep, decision-directed, signature-primitive-based approach that follows the current imaging technique with two layers of complex spatial matched filtering, one for final detection and one for classification, as described at the end.