Magnetic anomaly detection via a combination approach of minimum entropy and gradient orthogonal functions

Jiaqi, Zhou; Wang, Chengdong; Genzhai, Peng; Huan, Yan; Zhihong, Zhang; Chen, Yong

doi:10.1016/j.isatra.2022.08.026

Cited by 8 publications

(2 citation statements)

References 26 publications

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“…This process aims to identify a range of magnetic targets [7][8][9]. Magnetic anomaly detection can be divided into two approaches: incorporating digital signal processing methods into magnetic anomaly data processing, such as detection algorithms based on standard orthogonal basis function decomposition [10], and introducing magnetic gradient tensor matrices, which is currently a hot topic in this research field. Previous studies have mostly focused on the utilization of the magnetic gradient tensor matrix itself and the matrix's eigenvalues and eigenvectors.…”

Section: Introductionmentioning

confidence: 99%

Magnetic Gradient Tensor Positioning Method Implemented on an Autonomous Underwater Vehicle Platform

Zeng,

Zhang,

Liu

et al. 2023

JMSE

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Underwater magnetic surveying serves as the fundamental prerequisite for detecting sensitive underwater targets and magnetically susceptible submerged objects. However, when utilizing magnetic gradient tensor measurements for underwater positioning, the stability of the measurement apparatus can be significantly affected by hydrodynamic disturbances in the underwater environment, thereby having a substantial impact on data quality. Autonomous Underwater Vehicles (AUV) are unmanned underwater robots designed to independently perform various tasks and operations in underwater environments. In order to ensure the quality of data collection, this paper proposes a structure utilizing an Autonomous Underwater Vehicles platform equipped with a three-component magnetic gradiometer. This structure employs second-order tensor positioning algorithms and vertical gradient positioning algorithms, coupled with the Autonomous Underwater Vehicles’s inherent vertical profile motion, to effectively achieve the precise positioning of underwater cables. Simulation results indicate that, in the absence of geomagnetic background noise, both horizontal and vertical structures yield favorable positioning results. However, when introducing background noise of 40,000 nT, the horizontal structure exhibits larger positioning errors, whereas the vertical structure demonstrates smaller errors. Experimental results show that in near-field scenarios, both structures achieve relatively similar positioning accuracy. Nevertheless, under identical distances in the far field, the vertical structure reduces errors by a minimum of 30.78% compared to the horizontal structure, thereby confirming the feasibility of integrating magnetic gradient tensor measurement structures with Autonomous Underwater Vehicles platforms.

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Section: Introductionmentioning

confidence: 99%

Magnetic Gradient Tensor Positioning Method Implemented on an Autonomous Underwater Vehicle Platform

Zeng,

Zhang,

Liu

et al. 2023

JMSE

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show abstract

“…However, because the noise in the magnetic signal is primarily random noise, it is frequently essential to whiten the noise first, such as differential elimination of common-mode noise of two magnetometers or the development of high-order whitening filters. Since the Orthonormal Basis Function (OBF) is more suitable for white noise, and noise in a power frequency environment is mostly random, noise whitening is necessary before the application of the OBF method, such as differential elimination of common mode noise for two magnetometers [53].…”

mentioning

confidence: 99%

PFMD: A Power Frequency Magnetic Anomaly Signal Detection Scheme Based on Synchrosqueezed Wavelet Transform

Tian

Wen

et al. 2022

Applied Sciences

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Magnetic anomaly signal detection (MASD) is a passive method for the detection of visually obscured ferromagnetic objects. This paper proposes a new method for MASD based on the ambient field of power frequency magnetic (power transmission line system). Moreover, a new information extraction technique is extended by employing Synchrosqueezed Wavelet Transform (SSWT) to improve the accuracy of the MASD method. With the extended information extraction technique, the time-frequency information of the anomalies can be efficiently distinguished from the power frequency magnetic anomaly signal. The multi-component of the time-frequency information is separated by extracting the time-frequency ridges in the spectrogram. The complexity of time-frequency information is evaluated using Rayleigh entropy. Compared with the continuous wavelet transform and short-time Fourier transform, the Rayleigh entropy of our method is reduced by 4.1886 and 4.3623, respectively. Finally, the efficiency of the new method is verified by the outfield experiments.

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Airborne magnetic anomaly detection based on Bi-stable stochastic resonance system

Dai,

Chen,

Liu

et al. 2024

Measurement

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Magnetic anomaly detection via a combination approach of minimum entropy and gradient orthogonal functions

Cited by 8 publications

References 26 publications

Magnetic Gradient Tensor Positioning Method Implemented on an Autonomous Underwater Vehicle Platform

Magnetic Gradient Tensor Positioning Method Implemented on an Autonomous Underwater Vehicle Platform

PFMD: A Power Frequency Magnetic Anomaly Signal Detection Scheme Based on Synchrosqueezed Wavelet Transform

Airborne magnetic anomaly detection based on Bi-stable stochastic resonance system

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