Abstract
Underwater communication is highly challenging due to natural and anthropogenic noise in the ocean. The noise-corrupted signal should be denoised before being employed for further processing. This paper introduces an optimal cascaded adaptive filter structure using a Sign Data Least Mean Square (SDLMS) algorithm to denoise a noisy signal with maximum accuracy. Multiple stages are automatically added in the proposed filter structure, and the step size at every stage is varied. The proposed Multistage Sign Data LMS adaptive filter model has been evaluated for denoising an underwater fin whale sound signal corrupted by underwater vessel noise taken from the ShipsEar database. The simulation results prove that the proposed filter model performs remarkably well and offers a cost-effective hardware implementation of Adaptive Noise Canceller (ANC).
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
