Feature extraction method for self-adapting stochastic resonance type seismic waves

A stochastic resonance and feature extraction technology, applied in seismic signal processing, etc., can solve the problems of inability to extract weak signals from strong background noise and difficulty in extraction performance, and achieve the effect of improving signal energy and local signal-to-noise ratio

Inactive Publication Date: 2018-09-18
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

[0004] Traditional detection and extraction methods of line spectrum features of underwater targets, such as filtering, correlation detection, time-frequency analysis, etc., can handle noise with a certain signal-to-noise ratio, but it is very difficult to extract performance under strong background noise interference, and cannot Extract weak signals from

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  • Feature extraction method for self-adapting stochastic resonance type seismic waves
  • Feature extraction method for self-adapting stochastic resonance type seismic waves
  • Feature extraction method for self-adapting stochastic resonance type seismic waves

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Embodiment Construction

[0022] The present invention will be further described below in conjunction with the accompanying drawings and embodiments, and the present invention includes but not limited to the following embodiments.

[0023] The invention establishes a stochastic resonance signal detection system with an adaptive step size, and at the same time, aims at the problem of unknown characteristic frequency, and establishes a search and extraction method for frequency matching.

[0024] Specifically include the following steps:

[0025] Step 1: Noise Strength Estimation

[0026] The maximum likelihood estimation method is used to estimate the noise intensity, that is, the variance when there is only noise input, and the calculation formula is as follows:

[0027]

[0028] in, is the variance of the noise, N is the number of signal points, and T(x) is the test statistic;

[0029] Step 2: Stochastic Resonance System Construction Design

[0030] Set up a second-order nonlinear bistable sto...

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Abstract

The invention provides a feature extraction method for self-adapting stochastic resonance type seismic waves. The feature extraction method comprises the following steps: estimating noise intensity byvirtue of maximum likelihood estimation, establishing a second-order nonlinear bistable stochastic resonance system, and realizing noise matching and frequency matching by optimizing output signal tonoise ratio gain measure and synchronizing Cramers escape rate; and changing the signal frequency according to a preset step length, selecting a maximum signal to noise ratio value as an optimal matching value, and extracting the corresponding signal frequency, namely a target characteristic line spectrum frequency. According to the method, the signal energy and the local signal to noise ratio ata target characteristic line spectrum can be substantially increased, and characteristic signals completely drown in noise can be obviously enhanced and output.

Description

technical field [0001] The invention relates to the fields of underwater seismic wave signal extraction and weak signal detection. Background technique [0002] With the continuous improvement of measures such as degaussing and noise reduction of large underwater vehicles, their own self-protection capabilities continue to improve, especially for underwater moving targets such as quiet underwater vehicles such as unmanned submersibles, whose acoustic characteristics are constantly weakened. The difficulty of traditional acoustic detection methods increases. A ship sailing in water is a large energy carrier, which can release energy into the water body and spread outward through the disturbance of the hull to the water body, the natural frequency vibration of the hull, the mechanical vibration radiation noise on board, the propeller noise, and the hydrodynamic noise. Theory and experiments have proved that the unbalanced rotating parts of the moving ship, the periodic water ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01V1/30
CPCG01V1/30
Inventor 王海燕马石磊董海涛申晓红锁健
Owner NORTHWESTERN POLYTECHNICAL UNIV
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