Magnetic Anomaly Signal Space Analysis and Its Application in Noise Suppression

Yang, Liu; Liu, Zhongyan; Pan, Mengchun; Zhang, Qi; Chen, Dixiang; Chen, Wan; Gui, Hu; Zhang, Dewen; Chen, Zhuo

doi:10.1109/lgrs.2018.2869397

Cited by 17 publications

(3 citation statements)

References 7 publications

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“…Therefore, MAD is a technology for distinguishing a weak anomaly generated by a target from external magnetic noise and geomagnetic field. Recently, researchers have proposed several methods of MAD [12][13][14][15][16][17][18]. Zhou [19] proposed a trend filtering based on empirical mode decomposition (EMD) for MAD.…”

Section: Introductionmentioning

confidence: 99%

“…In this method, the scalar magnetic anomaly signal generated by the target is decomposed into three OBFs and the coefficients of each function are used to reveal the magnetic anomaly. In considering the noise energy in the coefficients, Liu [14] analyzed the constraint of coefficients in the space distribution and proposed an improved OBF method for MAD based on space projection transformation of coefficients. As we know that ambient geomagnetic field varies with time, the detection performance of the OBF method based on one scalar magnetometer will be affected by temporal geomagnetic variations.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Gradient signals analysis of scalar magnetic anomaly using orthonormal basis functions

Fan¹,

Kang²,

Hu³

et al. 2020

Meas. Sci. Technol.

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Magnetic anomaly detection is a passive and effective approach for detecting magnetic targets. During detection using one scalar magnetometer, temporal magnetic variations will affect the detection performance. In order to reduce the influence of magnetic variations on detection, we focus on the analysis of magnetic gradient signals and obtain four orthonormal basis functions (OBFs) of gradient signal. Based on the set of OBFs, we propose an improved method using the magnetic gradient signal. Meanwhile, we can also obtain the bearing of the target relative to the survey line in the method. The proposed method is validated by simulation and real-world magnetic noise. The results show that the proposed method has a good detection performance with low signal to noise ratio. Therefore, the proposed method can improve the detection probability of weak magnetic anomalies and also determine the bearing of targets relative to the survey line.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Gradient signals analysis of scalar magnetic anomaly using orthonormal basis functions

Fan¹,

Kang²,

Hu³

et al. 2020

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…Recently, researchers have proposed several methods of magnetic anomaly detection [10][11][12][13][14][15][16][17][18][19]. These methods can be divided into two categories.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Magnetic Anomaly Detection Method with Ensemble Empirical Mode Decomposition and Minimum Entropy Feature

et al. 2020

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Due to the fast attenuation of the magnetic field along with the distance, the magnetic anomaly generated by the remote magnetic target is usually buried in the magnetic noise. In order to improve the performance of magnetic anomaly detection (MAD) with low SNR, we propose an adaptive method of MAD with ensemble empirical mode decomposition (EEMD) and minimum entropy (ME) feature. The magnetic data is decomposed into the multiple intrinsic modal functions (IMFs) with different scales by EEMD. According to a defined criterion, the magnetic noise and magnetic signal are reconstructed based on IMFs, respectively. Entropy feature of reconstructed magnetic signal is extracted based on the probability density function (PDF) of the noise which is updated by the reconstructed magnetic noise. Compared to the traditional minimum entropy method, the entropy feature extracted by the proposed method is more obvious. The magnetic anomaly is detected whenever the entropy feature drops below the threshold. Thus, it is effective for revealing the weak magnetic anomaly by the proposed method. The measured magnetic noise is used to validate the performance of the proposed method. The results show that the detection probability of the proposed method is higher with low input SNR.

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Weak magnetic anomaly signal detection based on the entropy of mixed differential signal

et al. 2021

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Magnetic anomaly detection is of great significance in geological exploration and underwater target detection. However, the magnetic anomaly signal is not easy to be detected because of its weakness relative to the magnetic environmental noise, and the detection probability of the magnetic anomaly signal is affected by signal frequency. We propose a mixed differential minimum entropy method which can detect the weak magnetic anomaly signal. The proposed method combines the coherence difference method with the synchronous reference subtraction method in preprocess, which can suppress common-mode noise in the signal and relax the limitation of the frequency of the magnetic anomaly signal on the detection ability. Using the concept of entropy to describe the preprocessed signal can eliminate the residual high-frequency noise and further improve the signal-to-noise ratio of the target signal. Results show that the proposed method may effectively improve the signal-to-noise ratio and increase the frequency range of the magnetic anomaly signal, which has better detection performance than that of traditional method.

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Magnetic Anomaly Signal Space Analysis and Its Application in Noise Suppression

Cited by 17 publications

References 7 publications

Gradient signals analysis of scalar magnetic anomaly using orthonormal basis functions

Gradient signals analysis of scalar magnetic anomaly using orthonormal basis functions

Adaptive Magnetic Anomaly Detection Method with Ensemble Empirical Mode Decomposition and Minimum Entropy Feature

Weak magnetic anomaly signal detection based on the entropy of mixed differential signal

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