A Novel Spatiotemporal Environment Perception Framework for Ocean Current Field

Ocean current fields contain complex spatial patterns and temporal evolution, which pose significant challenges for efficient environment perception. This paper proposes a novel spatiotemporal environment perception framework for ocean current fields based on reduced-order modeling. After preprocessing and valid-ocean masking, singular value decomposition is applied to historical current snapshots to extract dominant spatial modes and form a compact low-rank representation. On this basis, two downstream tasks are considered. For spatial perception, sparse observations are used to reconstruct the full current field through least-squares estimation of modal coefficients. For temporal prediction, dynamic mode decomposition is introduced in the reduced-order coefficient space to perform one-step forecasting. Experimental results demonstrate that the proposed framework achieves accurate reconstruction from partial observations and effective short-term prediction, indicating that it can provide a compact and interpretable representation for unified spatiotemporal perception of ocean current fields.