Weak-Observation-Aware Multi-Object Tracking in Satellite Video with Temporal Evidence and Trajectory Reliability

Abstract

Multi-object tracking (MOT) in satellite video is fundamentally limited by low target observability: genuine targets often produce weak and unstable responses, while structured backgrounds can generate persistent target-like interference, leading to missed detections, fragmented trajectories, and identity switches. To address this ambiguity, we propose a weak-observation-aware and reliability-guided framework with a layered two-stage design: the front end enhances weak observations over short temporal windows, whereas the back end controls their use for long-term trajectory association and state updating according to their reliability. The front-end Temporal Prior Module (TPM) constructs a structure-aware temporal prior from motion-aligned historical evidence, strengthening weak-target responses while limiting the propagation of structured-background interference. The back-end Satellite Weak-Observation Reliability-Guided Tracker (SWRT) introduces active-track support into short-window reasoning and combines current, short-term, and long-term evidence into a candidate-reliability score that regulates association eligibility and state-update strength. On VISO, the proposed method achieves a multiple object tracking accuracy (MOTA) of 72.5% and an identity F1 score (IDF1) of 81.1%. On SATMTB-MOT, it achieves the best MOTA and IDF1 for airplanes and vehicles and remains competitive for ships among the compared methods. These results demonstrate that this layered design achieves a better balance between target recovery and identity preservation under low-observability conditions.