Underwater acoustic signal denoising method based on self-adaptive window filtering and wavelet threshold optimization

An adaptive window, underwater acoustic signal technology, applied in ultrasonic/acoustic/infrasonic transmission systems, character and pattern recognition, speech analysis, etc. problems such as small values, to achieve the effect of balancing the filtering performance and computational complexity, suppressing non-Gaussian impulse noise, and improving the suppression ability

Active Publication Date: 2020-09-18
QINGDAO UNIV OF SCI & TECH
View PDF11 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] However, in the actual ocean background noise environment, both Gaussian and non-Gaussian impulse noise are included, the wavelet threshold denoising method based on intelligent optimization is mainly used for Gaussian noise processing, it is difficult to directly apply to the comprehensive processing of oceanic underwater acoustic noise, and there are still a lot of problems. The disadvantages are specifically reflected in: firstly, t...

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Underwater acoustic signal denoising method based on self-adaptive window filtering and wavelet threshold optimization
  • Underwater acoustic signal denoising method based on self-adaptive window filtering and wavelet threshold optimization
  • Underwater acoustic signal denoising method based on self-adaptive window filtering and wavelet threshold optimization

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0143] see figure 1 As shown, the underwater acoustic signal denoising method based on AWFM+GDES under a Gaussian / non-Gaussian impulse noise environment described in this embodiment includes the following steps:

[0144] S1: Combine SαS distribution and normal distribution model to describe Gaussian / non-Gaussian impulse noise in the underwater acoustic channel; the specific steps are as follows:

[0145] S1-1: Signal receiving model:

[0146] For the single-transmission and single-reception underwater acoustic communication system, the time-domain signal y(t) received by the receiving end is expressed in digital form, and expressed as a set of discrete samples:

[0147] y(i)=s(i)+e(i), i=1,2,...,N

[0148] where s(i) is the noise-free desired signal with random amplitude and phase; e(i) is the additive ocean background noise; N is the number of samples;

[0149] S1-2: Gaussian / non-Gaussian impulse noise model:

[0150] The probability density function of the instantaneous ...

Embodiment 2

[0257] Embodiment 2: comparative analysis of simulation test results

[0258] In this embodiment, common underwater acoustic communication signals such as 2FSK, QPSK, and 16QAM signals are regarded as SOI, and additive Gaussian white noise and non-Gaussian impulse noise are combined into underwater acoustic noise to verify the performance of the present invention. Wherein the present invention is recorded as AWFM+GDES; The computer configuration used in simulation is: Intel i5-4570 processor, Windows 7 operating system, 4G internal memory, MATLAB R2015b.

[0259] The output SNR is defined as follows:

[0260]

[0261] The noise suppression ratio (NSR) is defined as follows:

[0262]

[0263] Among them, s(i) and are the expected signal and the estimated signal, respectively; and are the mean values ​​of the expected signal and the estimated signal, respectively, and N is the length of the signal.

[0264] Figure 5 The curves of output SNR versus input SNR after...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses an underwater acoustic signal denoising method based on self-adaptive window filtering and wavelet threshold optimization. The method comprises the steps: firstly, Gaussian/non-Gaussian pulse noise in an underwater acoustic channel is described by combining S[alpha]S distribution and a normal distribution model; a median filtering method based on a self-adaptive window is designed, the size of the filtering window is corrected according to the number of noise points in the window, and non-Gaussian pulse noise is restrained; then, based on an improved artificial bee colony method GDES-ABC, threshold parameters of a wavelet threshold denoising method are optimized, and the Gaussian noise suppression capacity is improved. According to the method, Gaussian/non-Gaussianpulse noise in a complex underwater acoustic environment can be effectively suppressed, the receiving capability of underwater acoustic communication signals such as 2FSK, QPSK and 16QAM is improved,and a relatively high output signal-to-noise ratio and a relatively high noise suppression ratio are obtained.

Description

technical field [0001] The invention belongs to the technical field of underwater acoustic signal denoising, and in particular relates to an underwater acoustic signal denoising method based on adaptive window filtering (AWFM) and wavelet threshold optimization (GDES) in a Gaussian / non-Gaussian impulse noise environment. Background technique [0002] Acoustic waves are widely used in the field of underwater communication. During underwater transmission and processing, the acoustic wave signal will be affected by underwater complex Gaussian / non-Gaussian pulse noise, resulting in degradation and distortion of the acoustic wave signal and a decrease in communication quality. Signal denoising technology is a signal processing method used to improve signal quality and reduce the impact of noise, and is widely used in underwater acoustic communication and other fields. [0003] For the sudden non-Gaussian impulse noise emitted by underwater seabed exploration, marine life, sea sur...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G10L21/0216H04B11/00G06K9/00G10L25/27G10L25/45
CPCG10L21/0216H04B11/00G10L25/45G10L25/27G06F2218/06
Inventor 王景景李嘉恒董新利杨星海施威徐凌伟郭瑛李海涛
Owner QINGDAO UNIV OF SCI & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap