Thermal wakes from small underwater vehicles reveal global patterns despite local similarity
Revealing Imaging Characteristics of Thermal Wakes from Underwater Vehicles Without Cooling-Water Discharge
Computer Vision and Pattern Recognition
Summary
Small underwater vehicles are hard to detect using traditional sonar or magnetic sensors. The authors show that these vehicles leave a thermal wake in the water’s surface temperature, but that the wake’s small parts look very similar to natural ocean patterns, making detection tricky. However, when looking at the whole wake, its overall shape follows the vehicle’s path, which differs from the background patterns caused by wind. This means detection methods need to focus on the bigger pattern rather than just tiny local signals.
What this means in practice
- •For maritime security teams: Detect small underwater vehicles by analyzing global thermal wake patterns rather than local features to improve surface surveillance accuracy.
- •For ocean monitoring operators: Forecast when and where thermal wakes are visible by integrating wake detection with ocean and atmospheric data, enhancing environmental monitoring.
Authors
Guoyi Zhang, Yanjin Du, Guangsheng Xu, Zhengyao Zhao, Siyang Chen, Jingjing Gao, Yuezheng Zhou, Yiyang Wu, Bin Wu, Tongsu Zhang, Lejia Ye, Donghe Wang, Jie Wang, Kaiye Hu, Zhipeng Ren, Han Wang, Boo Cheong Khoo, Xiangpeng Xu, Xiaohu Zhang
Abstract
Small uncrewed underwater vehicles are proliferating and threaten maritime security, yet evade sonar and magnetic sensors built for larger submarines. Infrared thermal wakes, generated by hydrodynamic displacement that modulates the cold-skin layer, offer a non-acoustic, non-magnetic alternative even without cooling-water discharge. Existing studies, however, rely on idealized simulations that fail to capture real-world backgrounds, offering limited guidance for target-background discrimination. We establish AVP-IR-Wake, the first large-scale, real-world, physically diverse benchmark of 161,485 frames collected over three years. We show that thermal wakes are extended structures of discrete vortices, violating the compactness assumption of conventional targets. We reveal local indistinguishability: individual wake vortices are statistically identical to wind-induced background vortices in temporal, frequency, and sparse domains, sharing low-frequency information and long-range correlations. This challenges the assumptions of compact, transient, high-frequency targets in conventional detection. Yet we establish global morphological separability: although locally inseparable, the wake as a whole is organized by vehicle trajectory, whereas background clutter is organized by wind-driven thermal fronts. This explains why representative detectors fail and shows that reliable detection must shift from local feature extraction to global trajectory-constrained physical modeling. Because the cold-skin layer varies globally and seasonally, forecasting wake observability will require integrating physical oceanography and atmospheric science, linking underwater surveillance to the changing ocean surface.