Impulse noise suppression underwater acoustic channel estimation method

Abstract

The invention provides an impulse noise suppression underwater acoustic channel estimation method, and belongs to the field of underwater acoustic signal processing. The invention relates to a method for suppressing impulse noise and realizing underwater acoustic channel estimation by using GAMP-SBL. The method comprises the following steps: (1) inputting a baseband receiving signal, a dictionary matrix, an iteration termination condition and related parameter initial values; (2) estimating impulse noise by using a GAMP-SBL (Generalized Amplitude Modulation Spatial Block Library); (3) subtracting the impulse noise estimation result from the baseband receiving signal; and (4) performing underwater acoustic channel estimation by using the GAMP-SBL. The method has the advantages that the sparsity of the impulse noise in the time domain is utilized, the impulse noise is estimated and subtracted from the baseband signal to suppress the impulse noise, damage to the signal structure can be reduced, and the impulse noise suppression performance is improved.

Description

technical field [0001] The present invention relates to an underwater acoustic signal processing method, in particular to an impulse noise suppression underwater acoustic channel estimation method, which utilizes generalized approximate message passing-sparse Bayesian learning (GAMP-SBL) to suppress impulse noise and realize underwater acoustic channel estimation. Methods for acoustic channel estimation. Background technique [0002] Under normal circumstances, the underwater acoustic channel estimation algorithm assumes that the background noise obeys the Gaussian distribution, but in some more complex underwater acoustic environments, the background noise may contain some impulse noise. In this case, the algorithm assuming Gaussian noise will suffer from impulsive noise and degrade performance. Conventional impulse noise suppression methods are difficult to set an appropriate filtering threshold, which is easy to destroy the structure of the signal, and has poor performan...

AI Technical Summary

Problems solved by technology

[0002] In general, underwater acoustic channel estimation algorithms assume that the background noise obeys a Gaussian distribution. However, in some more complex underwater acoustic environments, the background noise may contain some impulse noise

In this case, algorithms that assume Gaussian noise will suffer from impulsive noise and degrade performance

Conventional impulse noise suppression methods are difficult to set a suitable filtering threshold, easily destroy the signal structure, and have poor suppression performance on impulse noise

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