Underwater acoustic stealth & platform acoustics
Acoustic stealth design and underwater radiated noise (UWRN) control for submarines and surface platforms: acoustic signature management, sonar signal reflection and interference analysis, airborne noise estimation for crew comfort and operational readiness, and design optimisation for mast vibration and shock resilience.
Acoustic stealth engineering at Oravont →
Underwater radiated noise prediction →
SSR-Sim: target strength software →
Shock-mounting design against UNDEX shock →
Worked example: a submarine’s sonar echo →
Deep learning for vessel detection & underwater domain awareness
Deep-learning systems for underwater acoustics: detection, classification and recognition of underwater sound sources; classical signal processing (DEMON, envelope analysis) alongside self-supervised representation learning; physics-grounded synthetic acoustic datasets for model training and validation; and SKANN, a raw-waveform Selective-Kernel Acoustic Neural Network for open-set vessel re-identification. Oravont builds SKANN-based models for an organisation’s own recordings as a service, including offline deployment with no data egress.
SKANN and deep learning at Oravont →
Ship-radiated noise analysis and vessel re-identification →
Engineering software for naval design
Custom engineering software tools for naval defence applications, including SSR‑Sim (sonar signal reflection), Dhvanyakalan (submarine machinery noise), ABNContour (airborne-noise mapping) and SMS‑Suite (shock-mount simulation), available to defence organisations, shipyards and research institutions on enquiry.
Supervision & training
Supervision of doctoral and post-graduate research at the defence-technology interface, building on faculty tenures at DIAT and the Military Institute of Technology (MILIT), Pune; technical training and knowledge transfer in acoustics, vibration, and applied machine learning.
Each engagement draws on the same record: six years leading submarine acoustic stealth design at the Directorate of Submarine Design, a PhD in applied machine learning, and current research on deep learning for vessel detection directly from raw hydrophone waveforms. The publications and technical notes on this site show the methods at an unclassified level; the detail behind each service is on the Oravont pages linked from the cards.
Write to info@oravontsystems.com with the problem, the platform or data involved, and the timeframe.
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