Tag
This paper proposes Neural Radiated-Noise Fields (NRNF), a neural network approach for predicting underwater vehicle radiated noise spectra as a continuous function of 3D position, orientation, and frequency. Evaluated on lake trial data, the model achieves an average prediction error of 3.5 dB in the 50–5000 Hz band across multiple generalization settings.