Design And Development Of Autonomous Underwater Vehicles (AUVs) For Underwater Ambient Noise Validation.

The underwater soundscape is dominated by a complex mix of natural and anthropogenic noise, with commercial shipping noise (50–300 Hz) being the major low-frequency contributor, especially in shallow waters. The increasing demand for international shipping necessitates accurate measurement of this noise. AUVs, which are unmanned and operate autonomously, offer an ideal platform for this due to their ability to avoid surface wave interference.

Modeling UWAN, particularly in regions like the Indian Ocean, is challenging, often requiring custom technology and advanced techniques like Feedforward Neural Networks (FNN) and modified models (e.g., RANDI 3.1) that incorporate environmental, hydro-acoustic, and geo-acoustic data. The key challenges in AUV-based measurement include ensuring high hydrophone sensitivity, managing the vehicle's self-noise, and performing reliable calibration. AUV design involves complex mechanical, electrical, and software subsystems, utilizing various payloads like hydrophones, DVLs, and IMUs, and classifying vehicles by operating depth (Shallow, Mid-water, Deep-water, Gliders). Future research focuses on AUV swarm algorithms and real-time visual SLAM to enhance data collection and navigation.

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