Moving target detection in a maritime environment employing arbitrary rigid object motion autofocus

• Main Authors: Campbell, E. S., Garren, D. A.
• Format: Conference Proceeding
• Language: English
• Published: SPIE 13.06.2023
• ISBN: 1510661549; 9781510661547
• ISSN: 0277-786X
• DOI: 10.1117/12.2663202

Employment of SAR imagery is used to conduct surveillance of maritime vessels. Moving signatures from a ship cause azimuthal smearing in acquired images that can be exploited by autofocusing algorithms to conduct moving target detection (MTD). This study highlights the use of the Arbitrary Rigid Object Motion Autofocus (AROMA) algorithm employed within a sliding window to achieve autonomous detection of moving vessels within a given scene. AROMA is an extension of Phase Gradient Autofocus (PGA), an algorithm traditionally used in Autofocusing based MTD. AROMA is a three-dimensional generalization of the 1D PGA, using a physical signal model of the target relative to the imaging radar to compensate for phase errors and generating refocused imagery as if the target were stationary. Comparing refocused imagery to original unfocused images can yield a sufficient increase in image sharpness, indicating the presence of a moving target. This approach samples patches within a SAR image by sliding a window across the scene in a raster pattern, testing for moving targets within each window using AROMA. Effective sliding window algorithms employ overlapping patches to improve complete coverage of targets of interest. This often results in redundant target identifications, with the algorithm selecting multiple windows with partial or complete imagery of the same target. A consolidation algorithm is employed to select for a single window correlating to the max magnitude sum value of each target scatter, thus eliminating repeated outputs. This study tests the detection and false alarm rates of the AROMA based MTD approach compared to traditional methods.