Underwater Acoustic Signal Denoising Algorithms: A Survey of the State-of-the-art
It addresses the problem of improving underwater acoustic signal processing for applications like communication and monitoring, but it is a survey paper, so it is incremental in nature.
This paper reviews recent advances in underwater acoustic signal denoising, which is crucial for enhancing the reliability and clarity of underwater communication and monitoring systems, but it does not present new experimental results or concrete numbers.
This paper comprehensively reviews recent advances in underwater acoustic signal denoising, an area critical for improving the reliability and clarity of underwater communication and monitoring systems. Despite significant progress in the field, the complex nature of underwater environments poses unique challenges that complicate the denoising process. We begin by outlining the fundamental challenges associated with underwater acoustic signal processing, including signal attenuation, noise variability, and the impact of environmental factors. The review then systematically categorizes and discusses various denoising algorithms, such as conventional, decomposition-based, and learning-based techniques, highlighting their applications, advantages, and limitations. Evaluation metrics and experimental datasets are also reviewed. The paper concludes with a list of open questions and recommendations for future research directions, emphasizing the need for developing more robust denoising techniques that can adapt to the dynamic underwater acoustic environment.