Enhancing Anti-Submarine Warfare (ASW) Capabilities Through Adaptive AI-Driven Sonar Signal Processing: A Strategic Defense Approach
DOI:
https://doi.org/10.59890/ijetr.v4i2.6Keywords:
Anti-Submarine Warfare, Artificial Intelligence, Sonar Signal Processing, Maritime Defense, Underwater AcousticsAbstract
The increasing sophistication of submarine stealth technology has reduced the effectiveness of conventional sonar systems in Anti-Submarine Warfare (ASW). This study examines the role of adaptive Artificial Intelligence (AI) in enhancing sonar signal processing through a systematic literature review of studies published between 2019 and 2025. The analysis shows that AI-based approaches, including machine learning, deep learning, and Explainable Artificial Intelligence (XAI), significantly improve underwater target detection, classification accuracy, and real-time decision support. Hybrid AI models achieve classification accuracies above 90%, improve signal-to-noise ratios, and reduce false alarms in complex underwater environments. The findings indicate that AI-driven sonar systems can substantially strengthen future maritime defense capabilities by improving operational effectiveness, adaptability, and situational awareness.
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