Research on Noise Reduction Technology for Underwater Acoustic Signals Based on Adaptive Filtering
This article studies an adaptive filtering method based on Kalman filter optimization to improve the denoising performance of underwater acoustic signals.Firstly,an adaptive filtering method based on minimum mean square error was explored.Then,Kalman filtering is introduced to further optimize the filtering effect.Finally,this experiment was conducted on the MATLAB platform using the DeepShip dataset for method testing.The experimental results show that the method proposed in this paper is significantly superior to traditional methods in noise reduction of signals from different types of ships,with an average improvement of 5.2 dB in signal-to-noise ratio,verifying the effectiveness and superiority of this method.
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