Three-Dimension Polarimetric Correlation Pattern Interpretation Tool and Its Application

• Published in: IEEE transactions on geoscience and remote sensing 2022, Vol.60, p.1-1
• Main Authors: Li, Ming-Dian, Xiao, Shun-Ping, Chen, Si-Wei
• Format: Article
• Language: English
• Subjects: Angles (geometry); Clutter; Correlation; Detection; Differential geometry; Dimensions; Domains; Electromagnetic scattering; Ellipticity; Feature extraction; Marine vehicles; Orientation; polarimetric radar; polarimetric rotation domain; Polarization; Radar; Radar polarimetry; Rotation; SAR (radar); Scattering; ship detection; Spaceborne radar; superpixel; Synthetic aperture radar
• ISSN: 0196-2892; 1558-0644
• DOI: 10.1109/TGRS.2022.3222691

Polarimetric radar can acquire complete polarization information and is widely used in many applications. However, target orientation relative to the radar line of sight usually exhibits significant influences on the scattering mechanisms. Recently, such target scattering diversity has been successfully characterized and utilized with the polarimetric rotation domain interpretation techniques. In radar polarimetry, target scattering responses are affected by both polarization orientation angle and polarization ellipticity angle. In this vein, this work aims at exploring and utilizing the complete target scattering diversity by extending polarimetric rotation domain techniques to the polarization ellipticity angle dimension. The main idea is to develop a three-dimension polarimetric correlation pattern (3-D PCP) interpretation tool, which can visualize and exhibit targets' polarimetric rotation domain properties in terms of both the polarimetric orientation and ellipticity angles. Then, a set of global, local, and mutual polarimetric features are proposed to characterize the responses of a 3-D PCP interpretation tool. Especially, the curvatures in differential geometry are first introduced to describe the properties of the 3-D surface. The performance of these new polarimetric features is investigated with spaceborne polarimetric synthetic aperture radar (PolSAR) data. Experimental results demonstrate the advantage of the proposed 3-D PCP features in enhancing the target clutter ratio (TCR), especially for the weak ship area. Based on this, a non-local superpixel-level contrast measure (NSLCM) method for ship detection is proposed. Pure sea samples can be determined adaptively for salient map construction. Comparison results demonstrate better detection performance for both the inshore dense ship area and weak ship area.