DSSA-RT-DETR: Dynamic Scattering-Aware SAR Ship Detection for Complex Backgrounds and Small Targets

Synthetic aperture radar (SAR) supports all-weather maritime surveillance, but variations in ship scale, orientation, and scattering, together with sea clutter and coastal infrastructure, can cause missed small ships and false alarms. We propose DSSA-RT-DETR, a dynamic scattering-aware and spatially aligned variant of RT-DETR for SAR ship detection. Its scattering-aware dynamic Inception mixer block (SDIMB) combines multiscale square kernels with matched horizontal and vertical strip-convolution branches. The transposed directional supports provide a symmetry-inspired, axis-balanced operator basis, while independent input-dependent weights preserve orientation adaptivity. Local scattering differences condition the branch weights, making the effective operator sample- and position-dependent. LID-AIFI calibrates the global-attention residual according to local neighborhood differences, and SAF-CCFF aligns upsampled semantic features with shallow spatial details before cross-scale fusion. Controlled ablations support the three modifications. DSSA-RT-DETR achieves 97.55% mAP50, 72.65% mAP50:95, and 71.30% APsmall on SSDD, and 90.95% mAP50, 65.83% mAP50:95, and 67.90% APsmall on HRSID, with 13.471 M parameters and 46.5 GFLOPs. The results show improved aggregate and small-target detection after dataset-specific training, while the symmetry interpretation remains a structural inductive bias rather than an independently isolated accuracy contribution.