Recently, many techniques have been proposed to enhance the quality of radar images obtained using SAR and/or ISAR. These techniques include spatially variant apodization (SVA), adaptive sidelobe reduction (ASR), the Capon method, amplitude and phase estimation of sinusoids (APES) and data extrapolation. SVA is a special case of ASR; whereas the APES algorithm is similar to the Capon method except that it provides a better amplitude estimate. In this paper, the ASR technique, the APES algorithm and data extrapolation are used to generate radar images of two experimental targets and an airborne target. It is shown that although for ideal situations (point targets) the APES algorithm provides the best radar images (reduced sidelobe level and sharp main lobe), its performance degrades quickly for real world targets. The ASR algorithm gives radar images with low sidelobes but at the cost of some loss of information about the target. Also, there is not much improvement in radar image resolution. Data extrapolation, on the other hand, improves image resolution. In this case one can reduce the sidelobes by using non-uniform weights. Any loss in the radar image resolution due to non-uniform weights can be compensated by further extrapolating the scattered field data.