Researchers propose an occlusion-robust target tracking framework for defense and surveillance applications. The framework integrates YOLOv11n object detection, Kalman Filter motion prediction, and occlusion-aware appearance-based re-identification to maintain target identity and trajectory continuity under full and long-term occlusion. Benchmarked against OccluTrack, the framework achieves significant improvements in Multiple Object Tracking Accuracy and Identity F1 Score.