Characterization and statistical modeling of phase in single-channel synthetic aperture radar imagery

Traditionally, the phase content in single-channel synthetic aperture radar (SAR) imagery is discarded. This practice is justified by conventional radar resolution theory, which is a theory strictly relevant to point targets. The advent of high-resolution radars permits small targets previously considered to be points to be now treated as extended targets, in which case this theory is not strictly applicable. With this in mind, this paper offers a new insight into the relevance of phase in single-channel SAR imagery. The proposed approach builds on techniques from the fields of complex-valued and directional statistics. In doing so, three main contributions are presented, the first being a novel method for characterizing the phase content. Second, a new statistical model for the phase is considered, and then a set of 15 solely phase-based features are discussed. Our results are demonstrated on real-world SAR datasets for ground-truthed targets. The statistical significance of the information carried in the phase is clearly demonstrated. Furthermore, if applied to a dataset with higher resolution, the proposed techniques are expected to achieve even higher performance.