Enhancing Underwater Acoustic Noise Reduction Method With Advanced Noise Reduction Techniques

Underwater acoustic classification is a challenging task due to substantial ambient noises and complicated sound transfer pathways in the aquatic environment. This neccsites the need for noise elimination in subsurface acoustic signal handling. Due to the challenges faced by marine ecosystem and unique characteristics of undersea acoustic channels, suppression of undersea acoustical waves remains an important task in the area of aquatic acoustical signal manipulation. The proposed approach provides a remedy for reducing noise by utilizing the LMS filter in the initial phase and the RLS filter in the subsequent phase, which aids in the extraction of noises and signalling features for classification via ANIFS systems. The proposed approach incorporates noise mitigation and categorization, which may enhance the system's predictive reliability over 95% with a Root Mean Square (RMS) score of 0.7. As a result, the suggested approach outperforms other methods for noise suppression and classifications.