Publications

Automatic or assisted target recognition (ATR) is an important application of synthetic aperture radar (SAR). Most ATR researchers have focused on the core problem of declaration-that is, detection and identification of targets of interest within a SAR image. For ATR declarations to be of maximum value to an image analyst, however, it is essential that each declaration be accompanied by a reliability estimate or confidence metric. Unfortunately, the need for a clear and informative confidence metric for ATR has generally been overlooked or ignored. We propose a framework and methodology for evaluating the confidence in an ATR system's declarations and competing target hypotheses. Our proposed confidence metric is intuitive, informative, and applicable to a broad class of ATRs. We demonstrate that seemingly similar ATRs may differ fundamentally in the ability-or inability-to identify targets with high confidence.

Foliage penetrating (FOPEN) synthetic aperture radar (SAR) systems are capable of producing images of targets concealed under a foliage canopy. The quality and interpretability of these images, however, is generally limited by dense foliage clutter and by fundamental foliage-induced image degradation. Use of a polarimetric SAR to provide multiple polarization channels can mitigate these effects by offering target and scene information beyond that provided by a single-polarization SAR. This paper presents the results of a literature survey to investigate the use of multiple-polarization data in conjunction with FOPEN SAR applications. The effects of foliage propagation on SAR image quality are briefly summarized. Various approaches to multiple-polarization-based FOPEN target detection are described. Although literature concerning FOPEN target recognition is scarce, the use of multiple-polarization data for in-the-clear target recognition is described. The applicability of various target detection and recognition applications for use with concealed target SAR (CTSAR) imagery is considered.