Online Robust Low-Rank Enhancement and Structure-Aware Tracking for PPI Images from Marine Radar Displays

Marine radar plan position indicator (PPI) images may be the only observation source available for image-domain post-processing, yet weak target-like echoes are often obscured by sea clutter and persistent structural returns. Missed detections can fragment tracks, whereas permissive front-end processing can generate excessive candidates. This study presents an online robust low-rank enhancement and structure-aware tracking method. A finite history window supports background estimation by Huber iteratively reweighted projection, and raw intensity, local contrast, energy, and positive sparse-residual evidence are fused to generate ordered-statistics constant false alarm rate (OS-CFAR)-type candidates. Structural occupancy, compact-echo protection, multi-evidence aggregation, and multi-window motion cues then suppress structure-induced pseudo-motion. Active-track-first association, two-stage reassociation, and constrained candidate recovery are used to preserve track continuity. Across three PPI sequences acquired at different times at one radar site, structure-aware processing reduced the mean candidate load from 61.16 to 19.01 per frame. Against frame-by-frame dense visual references, the complete method achieved an F1 score of 88.24% and a multiple object tracking accuracy (MOTA) of 76.09%. The results show that, under the evaluated image-domain conditions, the method balances weak-echo retention, suppression of structure-induced false activations, and track continuity. Generalization across devices, sites, and sea states remains to be established.