Online Reference Template Adaptation for Robust LiDAR-Based Pose Tracking of Non-Cooperative Targets

Discrepancies between geometric priors and LiDAR observations can limit pose tracking of non-cooperative targets. This paper proposes online reference template adaptation that incorporates observations selected through registration-quality, incident-angle, and temporal-support criteria into a CAD-derived template. Two numerical simulations with known pose ground truth and two ground-based experiments evaluate the method under target rotation and close-range approach. In the approaching simulation, online adaptation reduces translation and rotation RMS errors from 1.44 to 0.52 cm and from $1.{10}^{\circ }$ to $0.{40}^{\circ }$, respectively. In the rotating simulation, the corresponding errors decrease from 4.61 to 4.37 cm and from $3.{97}^{\circ }$ to $3.{32}^{\circ }$. In the ground-based rotational experiment, online adaptation achieves a mean registration RMSE of $3.29\mathrm{cm}$, approximately 31% lower than the fixed CAD baseline and close to the offline reconstructed baseline ($3.05\mathrm{cm}$), while reducing threshold exceedances from 32 to four isolated frames. In the close-range experiment, roll estimates remain comparatively stable as the visible region shrinks, whereas the fixed CAD baseline exhibits more than ${10}^{\circ }$ of roll drift. These results support improved pose accuracy in the tested simulations and greater tracking stability in the ground-based experiments, without dedicated prior multi-view reconstruction.