  SSP distribution is an important parameter for underwater positioning,
navigation and timing (PNT) because it affects the propagation mode of
underwater acoustic signals. To accurate predict future sound speed
distribution, we propose a hierarchical long short--term memory (H--LSTM)
neural network for future sound speed prediction, which explore the
distribution pattern of sound velocity in the time dimension. To verify the
feasibility and effectiveness, we conducted both simulations and real
experiments. The ocean experiment was held in the South China Sea in April,
2023. Results show that the accuracy of the proposed method outperforms the
state--of--the--art methods.
