Active Acoustic Remote Sensing of Ocean Sound Speed Fields Along a Survey Track Using Inversion Constrained by Acoustic Propagation

The ocean sound speed profile (SSP) governs underwater acoustic propagation but remains difficult to observe continuously along a moving survey track using direct profiling instruments. This paper investigates differential acoustic propagation delays as remote observations that integrate propagation information along the acoustic paths for SSP retrieval along a survey track. A single vessel transmits coded signals, and a towed array records direct arrivals and arrivals reflected from the seabed. Their differential delays, together with water depth, are inverted using a physics-guided delay-denoising artificial neural network (PDANN), in which the SSP is represented by empirical orthogonal functions and constrained through a differentiable acoustic propagation model. Under 10 ms Gaussian delay perturbations, PDANN achieved an SSP RMSE of 0.611 m/s compared with 1.210 m/s for AETNN and 2.367 m/s for an ANN trained on clean data. Adding the Physical Module reduced the SSP RMSE from 0.759 to 0.611 m/s and the forward prediction RMSE for acoustic delays from 2.020 to 0.998 ms. Independent field evaluation using available CTD and XBT references yielded SSP errors of approximately 0.65 to 1.4 m/s. Sequential inversions further produced a spatially continuous representation of sound speed along the track. These results support active acoustic remote sensing as a practical approach for rapid SSP retrieval along a survey track under the tested configuration using a single vessel.