Mainlobe jamming suppression via improved BSS method for rotated array radar

Zhang, Hailong; Zhang, Gong; Biao, Xue; Yuan, Jiawen

doi:10.23919/jsee.2022.000129

Cited by 2 publications

(1 citation statement)

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“…Using the observed signal to separate the effective signal and noise is a problem of blind source separation. Blind source separation problem is that only the observed mixed signal is used to recover the source signal when both the source signal and transmission channel are unknown During signal transmission (Zhang et al, 2022). Independent component analysis (ICA) is one of the most effective and widely-used methods for solving this problem.…”

Section: Introductionmentioning

confidence: 99%

Joint denoising method of seismic velocity signal and acceleration signals based on independent component analysis

Zhang

et al. 2023

Front. Earth Sci.

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The signal-to-noise ratio (SNR) of seismic data is the key to seismic data processing, and it also directly affects interpretation of seismic data results. The conventional denoising method, independent variable analysis, uses adjacent traces for processing. However, this method has problems, such as the destruction of effective signals. The widespread use of velocity and acceleration geophones in seismic exploration makes it possible to obtain different types of signals from the same geological target, which is fundamental to the joint denoising of these two types of signals. In this study, we propose a joint denoising method using seismic velocity and acceleration signals. This method selects the same trace of velocity and acceleration signal for Independent Component Analysis (ICA) to obtain the independent initial effective signal and separation noise. Subsequently, the obtained effective signal and noise are used as the prior information for a Kalman filter, and the final joint denoising results are obtained. This method combines the advantages of low-frequency seismic velocity signals and high-frequency and high-resolution acceleration signals. Simultaneously, this method overcomes the problem of inconsistent stratigraphic reflection caused by the large spacing between adjacent traces, and improves the SNR of the seismic data. In a model data test and in field data from a work area in the Shengli Oilfield, the method increases the dominate frequency of the signal from 20 to 40 Hz. The time resolution was increased from 8.5 to 6.8 ms. The test results showed that the joint denoising method based on seismic velocity and acceleration signals can better improve the dominate frequency and time resolution of actual seismic data.

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Section: Introductionmentioning

confidence: 99%