TECHNICAL PANEL

The field of underwater acoustics is rapidly evolving, offering a dynamic environment where theory and practice meet to address real-world challenges. This Technical Panel aims to bring together system designers, researchers and practitioners to investigate the evolving landscape of metrology for underwater acoustics, focusing on modeling and signal processing methodologies. Capturing the dynamicity and heterogeneity of the underwater domain, where the deep interactions among propagation, scattering and ambient noise require complicate modeling and experimental validation, is a growing need as new applications emerge, from autonomous navigation to environmental monitoring and distributed sensing.

The guiding questions to be explored in this panel are as follows:

• How can metrological traceability be ensured in highly variable and poorly observable underwater environments?
• What modeling approaches best capture the interplay between propagation physics, environmental dynamics, and measurement uncertainty?
• Which signal processing strategies enable robust estimation under low SNR, non stationary, or data sparse conditions?
• How should machine learning tools be validated to meet metrological standards of reliability and interpretability?
• What frameworks are needed to harmonize measurements across heterogeneous platforms and missions?

• Establish a shared metrological framework for underwater acoustics by clarifying definitions, measurement principles, and traceability requirements across diverse operational contexts.
• Assess the state of the art in modeling and signal processing, with particular attention to the interplay between environmental variability, propagation physics, and measurement uncertainty.
• Evaluate the role of data driven and machine learning approaches within metrological workflows, ensuring standards of transparency, reproducibility, and interpretability.
• Promote interoperability and standardization across heterogeneous platforms and sensors, fostering a coherent ecosystem for underwater acoustic measurements.
• Stimulate interdisciplinary dialogue among physicists, engineers, metrologists and system designers.

1. Propagation Modeling and Environmental Dynamics
   • Modeling sound propagation in dynamic, uncertain, and poorly observable underwater environments;
   • Sensitivity analysis and environmental parameter estimation;
   • Integration of modeling approaches.
2. Signal Processing for Robust Estimation
   • Processing strategies for low SNR, non stationary, and sparse data scenarios;
   • Adaptive and model based estimation techniques;
   • Noise characterization and mitigation.
   • Uncertainty quantification and validation
3. Data Driven and Machine Learning (ML) Methodologies
   • Opportunities and limitations of ML in metrological contexts;
   • Requirements for interpretability, robustness, and verification.
4. Interoperability and System Level Integration
   • Standards for multi platform and multi mission measurement coherence;
   • Distributed sensing architectures and collaborative measurement strategies;
   • Metrology as an enabling layer for autonomous and networked systems.