Magnetic Anomaly Detection Research Articles

A Novel Strategy for Improving the Aeromagnetic Compensation Performance of Helicopters.

An aeromagnetic survey is an important method in magnetic anomaly detection and geophysical prospecting. The magnetic field is typically measured by optically pumped magnetometers (OPM) installed on the aircraft. The measurement accuracy of the OPM is easily affected by the platform-generated magnetic fields. Therefore, aeromagnetic compensation is necessary. The traditional compensation model only considers the permanent, induced, and eddy current interference magnetic field of the aircraft platform. However, the interference field produced by the avionics system, and the relative motion between the aircraft and the magnetometer, are still not taken into account. To address this issue, we proposed a novel strategy to eliminate the additional interference of the platform with two OPMs. Among them, the OPM located farther away from the aircraft serves as a sensing magnetometer, whereas the near OPM serves as a reference magnetometer. The coherent noise suppression method is used to process the residual magnetic field interference after compensation. By establishing the interference magnetic transfer function between the two sensors, the interference field can be suppressed. The results of the experiments demonstrate the effectiveness of the novel strategy, and the standard deviation of residual interference drops from 0.065 nT to 0.045 nT.

Magnetic anomaly detection based on stochastic resonance

Orthonormal basis function (OBF) decomposition method and minimum entropy (ME) detector are two typical methods of magnetic anomaly detection. The OBF detector works effectively only when the assumptions of the target signal and noise are appropriate, and the ME detector is limited by low signal-to-noise ratio (SNR). In order to improve magnetic anomaly detection performance in the case of low SNR and no prior information of the target signal, we proposed a novel detector by using stochastic resonance (SR) method and named it SR detector in the paper. The SR detector consists of a bistable SR system and a corresponding receiver. Firstly, the noise is used to enhance the magnetic anomaly signal with the help of SR system, instead of being suppressed in a traditional method; then the anomaly signal can be detected more effectively by the receiver. Experimental results show that the SR detector did work well, its detection probability approximated to 70% even if the input SNR was −3 dB, and was about 100% if the input SNR was 0dB, when the false alarm rate (FAR) was 1.5%. Furthermore, the SR detector provided higher detection probability than the ME detector under the same basis. In a word, due to the good detection performance and simple implementation, the SR detector would be more attractive in practice.

Adaptive filtering method for magnetic anomaly detection

Magnetic anomaly detection (MAD) is a technique applied in searching, localizing, and even tracking (if the target is moving) a ferromagnetic target of interest. Due to the complexity of the ambient magnetic field, almost all of the detection methods need a filter to be a preprocessing procedure. A typical way is passing the measured signal through a fixed frequency band that contains the frequency of the target signal. However, the target signal’s frequency is mostly determined by the movement velocity of the magnetometer and the distance from magnetometer to target. Namely, in different cases, the targets’ frequencies are different. We analyze the target model and represent the target signal with a single scalar variable. Through projecting the three-dimensional space into a two-dimensional plane, we lastly transform the target signal into a superposition of three sinusoids. Based on it, we propose a method to estimate the frequency band adaptively. Furthermore, we present an adaptive filtering method based on wavelet transform and take some simulation tests to prove that the proposed method has better performance compared with traditional filters.

Detection of vehicle tracks by a three-axis magnetometer

A novel approach for target tracking enabled by a magnetic anomaly detection (MAD) system with a single three-axis magnetic sensor is demonstrated. Twelve types of three-dimensional target MAD signals at a cross road were calculated using a magnetic dipole model. Characteristic features derived from Bxy curves were used to identify the type of tracks. A nonlinear non-diagonal three-axis giant magnetoimpedance sensor (GMI) was used to validate the model, which operated in range of ± 500 mGs with a noise level below RMS 200 pT at the frequency ranging from 0.1 to10 Hz. Experimental results showed that the identification by the model was in good agreement with real tracks.

Detection of Magnetic Anomaly Signal Based on Information Entropy of Differential Signal

Magnetic anomaly detection is an effective approach for detecting the visually obscured ferromagnetic target, and its performance is mainly limited by background geomagnetic noise. In contrast to the traditional detection methods that rely on several a priori assumptions regarding the target or the probability of magnetic noise consisting of external geomagnetic noise and intrinsic sensor noise, we present, in this letter, a new estimator of information entropy for differential signal acquired by a pair of magnetic sensors to detect any changes in the magnetic noise pattern. First, the magnetic noise probability density function (PDF) of differential signal is estimated by using the kernel smoothing method. Then, the minimum entropy detector based on the magnetic noise PDF of differential signal is used to detect the magnetic anomaly target. Finally, according to the probabilities of false alarm, the detection threshold can be obtained to be used for abnormal judgment. In order to verify the effectiveness of the proposed method, the experiment is conducted, and the results demonstrate that the proposed method has better detection performance than that of traditional methods.

Attitude control system proposed for SERPENS-2 space mission

SERPENS mission involves research and development of nanosatellites and is inserted in a set of activities carried on by Brazilian universities in the scope of strategies coordinated by AEB (Brazilian Space agency). The first satellite of a series, SERPENS-1, was put into orbit in September 2015, retiring in March 2016. SERPENS-2 mission is currently being designed. The experiments to be carried out in SERPENS-2 are: X and Gamma rays detection; South Atlantic magnetic anomaly detection and testing of a pulsed plasma thruster. Each experiment is related to the attitude. This paper is concerned with the Attitude Determination and Control System (ADCS) design of a 3U CubeSat. A proposal of ADCS for SERPENS-II mission is described concerning both the mission and the attitude requirements. The modeling of the satellite and of its attitude dynamics is preliminarily studied considering the proposed ADCS. Results of the first control mode (de-tumbling) are presented and meet the requirements, as expected. An initial development of the second control mode is also evaluated: an attitude regulator in the local horizontal local vertical frame, with pure magnetic actuation.

Using marine magnetic survey data to identify a gold ore-controlling fault: a case study in Sanshandao fault, eastern China

The Jiaodong Peninsula has the greatest concentration of gold ore in China and is characterized by altered tectonite-type gold ore deposits. This type of gold deposit is mainly formed in fracture zones and is strictly controlled by faults. Three major ore-controlling faults occur in the Jiaodong Peninsula—the Jiaojia, Zhaoping and Sanshandao faults; the former two are located on land and the latter is located near Sanshandao and its adjacent offshore area. The discovery of the world's largest marine gold deposit in northeastern Sanshandao indicates that the shallow offshore area has great potential for gold prospecting. However, as two ends of the Sanshandao fault extend to the Bohai Sea, conventional geological survey methods cannot determine the distribution of the fault and this is constraining the discovery of new gold deposits. To explore the southwestward extension of the Sanshandao fault, we performed a 1:25 000 scale marine magnetic survey in this region and obtained high-quality magnetic survey data covering 170 km2. Multi-scale edge detection and three-dimensional inversion of magnetic anomalies identify the characteristics of the southwestward extension of the Sanshandao fault and the three-dimensional distribution of the main lithologies, providing significant evidence for the deployment of marine gold deposit prospecting in the southern segment of the Sanshandao fault. Moreover, three other faults were identified in the study area and faults F2 and F4 are inferred as ore-controlling faults: there may exist other altered tectonite-type gold ore deposits along these two faults.

Magnetoelectric coupling of a magnetoelectric flux gate sensor in vibration noise circumstance

A magnetoelectric (ME) flux gate sensor (MEFGS) consisting of piezoelectric PMN-PT single crystals and ferromagnetic amorphous alloy ribbon in a self-differential configuration is featured with the ability of weak magnetic anomaly detection. Here, we further investigated its ME coupling and magnetic field detection performance in vibration noise circumstance, including constant frequency, impact, and random vibration noise. Experimental results show that the ME coupling coefficient of MEFGS is as high as 5700 V/cm*Oe at resonant frequency, which is several orders magnitude higher than previously reported differential ME sensors. It was also found that under constant and impact vibration noise circumstance, the noise reduction and attenuation factor of MEFGS are over 17 and 85.7%, respectively. This work is important for practical application of MEFGS in real environment.

Multi-functional piezoelectric/magnetostrictive laminated composite for AC and DC magnetic detection

We report on a fabrication of laminated magnetoelectrical composite Metglas/PMNT/Metglas, which is capable of detecting both ac and dc magnetic field. The ME charge coefficient αQ to ac magnetic field is obtained of 450 pC/Oe at quasi-static frequency under the optimal bias magnetic field and it shows a high value of Qm at resonant frequency. Meanwhile, the value of αQ of this ME sensor with small dimensions shows great sensitivity to dc magnetic field. In the magnetic range of 0.3–2.8 Oe, the sensitivity of αQ to Hdc reaches to 78 200 pC/Oe2 under the resonant working condition and the linearity is characterized as 3.3% FSO. Further, the small change of Hdc = 10 nT is detected using a lock-in amplifier under a drive magnetic field of Hac = 140 nT. Due to this kind of ME sensors published so far focus essentially on ac magnetic detection rather than dc magnetic field, the property of dc magnetic detection achieved here will broaden the application of ME sensors especially in magnetic anomaly detection.

Rotational speed measurement of ring spinning based on magnetic sensor

This study introduces a rotational speed measurement method based on magnetic anomaly detection to monitor the traveler’s speed in ring spinning. A structure and theoretical model of anomalous magnetic field detection were built. Rotational speed can be calculated from the output signal acquired through tunnel magnetoresistance. A testing system was developed to test sensor performance. The output signals of the sensor at different rotational speed, working gap, and fixed offset were experimentally investigated. The result showed that the proposed sensor can meet the rotational speed measurement requirement of ring spinning. Finally, the practical application of the sensor in a ring spinning machine was introduced. The result indicates that the system can satisfy the practical application of yarn break detection with the advantages of compact size, high sensitivity, strong anti-interference capability, good stability, high reliability, and so on. The method proposed in this paper has shown great potential in providing the production status of the spinning field.

Construction of an Overhauser magnetic gradiometer and the applications in geomagnetic observation and ferromagnetic target localization

The proton precession magnetometer with single sensor is commonly used in geomagnetic observation and magnetic anomaly detection. Due to technological limitations, the measurement accuracy is restricted by several factors such as the sensor performance, frequency measurement precision, instability of polarization module, etc. Aimed to improve the anti-interference ability, an Overhauser magnetic gradiometer with dual sensor structure was designed. An alternative design of a geomagnetic sensor with differential dual-coil structure was presented. A multi-channel frequency measurement algorithm was proposed to increase the measurement accuracy. A silicon oscillator was adopted to resolve the instability of polarization system. This paper briefly discusses the design and development of the gradiometer and compares the data recorded by this instrument with a commonly used commercially Overhauser magnetometer in the world market. The proposed gradiometer records the earth magnetic field in 24 hours with measurement accuracy of ± 0.3 nT and a sampling rate of 3 seconds per sample. The quality of data recorded is excellent and consistent with the commercial instrument. In addition, experiments of ferromagnetic target localization were conducted. This gradiometer shows a strong ability in magnetic anomaly detection and localization. To sum up, it has the advantages of convenient operation, high precision, strong anti-interference, etc., which proves the effectiveness of the dual sensor structure Overhauser magnetic gradiometer.

Resolution improvement of low frequency AC magnetic field detection for modulated MR sensors.

Magnetic modulation methods especially Micro-Electro-Mechanical System (MEMS) modulation can improve the sensitivity of magnetoresistive (MR) sensors dramatically, and pT level detection of Direct Current (DC) magnetic field can be realized. While in a Low Frequency Alternate Current (LFAC) magnetic field measurement situation, frequency measurement is limited by a serious spectrum aliasing problem caused by the remanence in sensors and geomagnetic field, leading to target information loss because frequency indicates the magnetic target characteristics. In this paper, a compensation field produced with integrated coils is applied to the MR sensor to remove DC magnetic field distortion, and a LFAC magnetic field frequency estimation algorithm is proposed based on a search of the database, which is derived from the numerical model revealing the relationship of the LFAC frequency and determination factor [defined by the ratio of Discrete Fourier Transform (DFT) coefficients]. In this algorithm, an inverse modulation of sensor signals is performed to detect jumping-off point of LFAC in the time domain; this step is exploited to determine sampling points to be processed. A determination factor is calculated and taken into database to figure out frequency with a binary search algorithm. Experimental results demonstrate that the frequency measurement resolution of the LFAC magnetic field is improved from 12.2 Hz to 0.8 Hz by the presented method, which, within the signal band of a magnetic anomaly (0.04-2 Hz), indicates that the proposed method may expand the applications of magnetoresistive (MR) sensors to human healthcare and magnetic anomaly detection (MAD).

Searching for prohibited items in mental-health hospitals: A randomised controlled trial of two metal-detecting technologies.

Weapons and other items with potential to cause harm are usually prohibited in mental-health hospitals and other psychiatric facilities. Detecting such prohibited items (PIs) can be problematic, particularly if concealed, and metal detectors are commonly used to search for such items. Our study compared two types of metal detection: continuous wave detection (CWD) by hand-held metal detector (HHMD) and magnetic anomaly detection (MAD) by a static pole device. In the study, real and dummy PIs were hidden on test subjects and in a simulated body cavity. The results showed MAD to be significantly superior to CWD in detecting small concealed PIs containing ferrous metal. The MAD pole found 100% of the real PIs on the test subjects and in the simulated body cavity. The CWD HHMD found only 5.2% of the real PIs, and these were limited to those on the test subjects, as it detected none in the simulated body cavity. In addition, the time taken to search by MAD pole was shorter than time taken to search by CWD HHMD.

Performance improvement of magnetic anomaly detector using Karhunen–Loeve expansion

In this work, the authors improve the magnetic anomaly detector by using Karhunen-Loeve expansion, for expanding the detection distance of visually obscured ferromagnetic object when the target signal is contaminated by coloured noise. In the detector, the orthonormal basis functions are modified by the autocorrelation function of geomagnetic noise, and the anomaly is detected by matched filtering. Compared with the traditional detector, simulation results show that the modified detector has better performance with coloured Gaussian noise; especially, the improvement is more evident when the noise exponent is bigger. The real geomagnetic noise is proved to be coloured and obey approximate Gaussian distribution by the measurements in experiment. Tests with this noise indicate that the proposed detector achieves an incremental detection probability of 0.1 - 0.2 in the case of low signal-to-noise ratio, which makes it more attractive in practice.

A Novel Detection Method for Underwater Moving Targets by Measuring Their ELF Emissions with Inductive Sensors.

In this article, we propose a novel detection method for underwater moving targets by detecting their extremely low frequency (ELF) emissions with inductive sensors. The ELF field source of the targets is modeled by a horizontal electric dipole at distances more than several times of the targets’ length. The formulas for the fields produced in air are derived with a three-layer model (air, seawater and seafloor) and are evaluated with a complementary numerical integration technique. A proof of concept measurement is presented. The ELF emissions from a surface ship were detected by inductive electronic and magnetic sensors as the ship was leaving a harbor. ELF signals are of substantial strength and have typical characteristic of harmonic line spectrum, and the fundamental frequency has a direct relationship with the ship’s speed. Due to the high sensitivity and low noise level of our sensors, it is capable of resolving weak ELF signals at long distance. In our experiment, a detection distance of 1300 m from the surface ship above the sea surface was realized, which shows that this method would be an appealing complement to the usual acoustic detection and magnetic anomaly detection capability.

Characterization and detection of oscillating magnetic dipole signals

The present paper deals with the problem of characterization of oscillating magnetic dipole (OMD) signals and the development of a suitable magnetic anomaly detection (MAD) algorithm for it. The resulting outcomes of investigating the above mentioned problem are: (1) a development of a complete model of the noise and the signal based on a non-linear gravity pendulum model. This model was compared and verified against real world magnetic signals, as well as simulated ones. (2) A detection algorithm that utilizes this model by whitening the noise and seeking for periodical features in the signal. The developed algorithm has high noise immunity with high detection probabilities even at as low SNR as −10 dB. Compared to benchmark detectors, our detection scheme offers performance improved by 5–10 dB. Moreover, when testing the detector against real world signals, the SNR difference in respect to the performance predicted by the simulations was less than 2.5 dB.

A new segmentation strategy for processing magnetic anomaly detection data of shallow depth ferromagnetic pipeline

Magnetic anomalies produced by underground ferromagnetic pipelines because of the polarization of earth's magnetic field are used to obtain the information on the location, buried depth and other parameters of pipelines. In order to achieve a fast inversion and interpretation of measured data, it is necessary to develop a fast and stable forward method. Magnetic dipole reconstruction (MDR), as a kind of integration numerical method, is well suited for simulating a thin pipeline anomaly. In MDR the pipeline model must be cut into small magnetic dipoles through different segmentation methods. The segmentation method has an impact on the stability and speed of forward calculation. Rapid and accurate simulation of deep-buried pipelines has been achieved by exciting segmentation method. However, in practical measurement, the depth of underground pipe is uncertain. When it comes to the shallow-buried pipeline, the present segmentation may generate significant errors. This paper aims at solving this problem in three stages. First, the cause of inaccuracy is analyzed by simulation experiment. Secondly, new variable interval section segmentation is proposed based on the existing segmentation. It can help MDR method to obtain simulation results in a fast way under the premise of ensuring the accuracy of different depth models. Finally, the measured data is inversed based on new segmentation method. The result proves that the inversion based on the new segmentation can achieve fast and accurate inversion of depth parameters of underground pipes without being limited by pipeline depth.

Geochemical survey of soil samples from the archaeological site Dromolaxia-Vyzakia (Cyprus), by means of micro-XRF and statistical approaches

During the 13th and 12th centuries BCE, Dromolaxia - Vyzakia (Hala Sultan Tekke) was a flourishing coastal settlement located at the shores of the Larnaca salt lake and for this reason the site has attracted a great deal of scholarly interest. Evidence of ceramic, ivory and metal manufacturing processes supports the belief that this site was not only a location active in trade, but also an important crafts centre. Despite the fact that a significant number of archaeological missions invested considerable time and expertise to study the site, its spatial extent and makeup is still not fully understood. Significant efforts are currently underway to reveal the extent of the whole settlement and to pinpoint possible anthropogenic activities. The detection of intriguing magnetic anomalies during a preliminary geophysical survey over an unexcavated area adjacent to the main excavation, and the presence of nearby surface scattered slag fragments, suggested further investigation. These locations were ideal for an extensive geochemical survey through micro-XRF measurements. Therefore, an extensive geochemical survey, the objective of this study, was carried out to measure concentrations of elements (K, Ca, Ti, Cr, Mn, Fe, Ni, Cu, and Zn) using a micro-XRF. Soil samples were collected at an excavated area of known anthropogenic activity as well as from other unexcavated areas including the one assessed by the geophysical survey. Results were analyzed with the method of principal components analysis (PCA) and Pearson's correlation coefficients focusing on the identification of possible patterns amongst sampling areas. The site's normal background concentration values (NBC) were also determined in order to evaluate elemental enhancement by enrichment factors. The statistical analysis of results indicated the impact of metalworking or other related processes in the soil's chemistry. In addition, it identified elements that can be attributed to anthropogenic activities (K, Ca, Ni, Cu, and Zn) and also corroborated with the geophysical data highlighting specific zones where future archaeological efforts should focus.

Compensation of Geomagnetic Vector Measurement System With Differential Magnetic Field Method

The accurate measurement of a geomagnetic field is a key technology in many applications, such as magnetic anomaly detection, underwater geomagnetic navigation, and motion tracking. However, the magnetic interference fields, such as ferromagnetic parts and other electric equipments, will seriously influence the measurement accuracy of geomagnetic vector measurement system, and thus should be compensated. In this paper, a new compensation method using differential magnetic field is proposed. As a first step, a permanent magnet with different relative positions is used to change the ambient magnetic field to construct the error model equations about unknown quantities, and the soft-iron error parameters can be estimated by solving equations with nonlinear least square method. Then, the hard-iron error parameters can be estimated by changing the fixation direction of the three-axis magnetometer. Finally, the estimated error parameters are used for compensating the magnetic interference field. In order to verify effectiveness of the proposed method, simulation and experiment are performed, and the results demonstrate that the proposed method estimates error parameters accurately and improves the measurement accuracy of geomagnetic vector measurement system greatly.

Drift Reduction in Pedestrian Navigation System by Exploiting Motion Constraints and Magnetic Field.

Pedestrian navigation systems (PNS) using foot-mounted MEMS inertial sensors use zero-velocity updates (ZUPTs) to reduce drift in navigation solutions and estimate inertial sensor errors. However, it is well known that ZUPTs cannot reduce all errors, especially as heading error is not observable. Hence, the position estimates tend to drift and even cyclic ZUPTs are applied in updated steps of the Extended Kalman Filter (EKF). This urges the use of other motion constraints for pedestrian gait and any other valuable heading reduction information that is available. In this paper, we exploit two more motion constraints scenarios of pedestrian gait: (1) walking along straight paths; (2) standing still for a long time. It is observed that these motion constraints (called “virtual sensor”), though considerably reducing drift in PNS, still need an absolute heading reference. One common absolute heading estimation sensor is the magnetometer, which senses the Earth’s magnetic field and, hence, the true heading angle can be calculated. However, magnetometers are susceptible to magnetic distortions, especially in indoor environments. In this work, an algorithm, called magnetic anomaly detection (MAD) and compensation is designed by incorporating only healthy magnetometer data in the EKF updating step, to reduce drift in zero-velocity updated INS. Experiments are conducted in GPS-denied and magnetically distorted environments to validate the proposed algorithms.