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Magnetic anomaly detection technologies have been widely used for tracking moving targets. In this paper, we present a fast-tracking method for magnetic abnormalities using a distributed Overhauser magnetometer system based on the genetic algorithm. Our proposed framework of the Overhauser magnetometer system employs multiple sensors to eliminate background interference, and the genetic algorithm efficiently solves magnetic anomaly data without requiring the derivation of the objective function. Test platforms were built to evaluate the distributed Overhauser magnetometer system and the genetic algorithm. Results from the natural outdoor magnetism laboratories showed that the noise of our presented magnetometers was below 0.134 nT. The optimal factors for solution precision and effectiveness in the genetic algorithm were obtained from the simulation. Moreover, the outdoor tracking experiments indicated that the proposed method could accurately and quickly detect the moving ferromagnetic object within 6.9% maximum positioning error in 0.55 m, and the tracking precision of the object velocity can get 5.88% maximum error in 4.33 km/h. [ABSTRACT FROM AUTHOR]

The magnetic anomalies generated by the ferromagnetic targets are usually buried within uncontrollable interference sources, such as the power frequency and random noises. In particular, the variability of the geomagnetic field and the low signal-to-noise ratio (SNR) of the magnetic anomalies cannot be avoided. In this paper, to improve the performance of magnetic anomaly detection (MAD) with a low SNR, we propose a novel structured low-rank (SLR) decomposition-based MAD method. In addition, a new framework based on the SLR and singular value decomposition (SVD) is constructed, dubbed SLR-SVD, and the corresponding working principle and implemented strategy are elaborated. Through comparing the SLR-SVD with two state-of-the-art methods, including principal component analysis and SVD, the results demonstrate that the proposed SLR-SVD can not only suppress the noise sufficiently, i.e., improving 55.26% approximately of the SNR, but also retain more boundary information of magnetic anomalies, i.e., decreasing approximately 68.05% of the mean squared error and improving approximately 28.47% of the structural similarity index. [ABSTRACT FROM AUTHOR]

Fluxgate sensors are currently widely used for weak magnetic field measurement because of their relatively great performance, such as resolution, power consumption, and measurement of vector magnetic fields directly. Since the analog fluxgate sensor has some drawbacks, e.g., it would be influenced by the noise of the analog circuit. Hence, in recent years, the analog circuit is gradually inclined to be realized by digital processing in which the software parameter adjustment is employed to replace the analog components, which can greatly improve the flexibility of the design. This paper proposes a digital single-axis fluxgate sensor according to the cobalt-based amorphous effect. To be specific, the analog signal output by the fluxgate is sampled directly by an analog-to-digital converter to obtain the signal waveform in digital form after amplification. The demodulation, filtering, and integration of the signal are all solved by mathematical algorithms. Based on the working principle of the fluxgate sensor, the selection of the magnetic core material and coil winding method of the fluxgate sensor probe is introduced in detail. The design and function of the excitation circuit and preamplifier circuit, as well as the specific realization of digital signal processing, are described. Finally, the performance test of the digital fluxgate sensor was performed under laboratory conditions, and the magnetic anomaly detection comparison experiment was performed outdoors with commercial fluxgate sensors. To sum up, the linearity of the digital single-axis fluxgate sensor is better than 1 × 10−5, and the root mean square noise value is below 0.1 nT. At the same time, it has good magnetic field tracking performance and is extremely sensitive to the magnetic field of the measurement area. [ABSTRACT FROM AUTHOR]

The low magnetic field measurement has been utilized since ancient times in order to find economic resources, to detect magnetic anomalies, etc. In this case, the vector magnetic survey can simultaneously obtain the modulus and direction information of the magnetic field, which can contribute to obtaining more precise information and characteristics of magnetic field resources. This paper is concerned with the potential to exploit the signals of vector magnetic field measurement with a magneto-inductive (MI) sensor. To evaluate the capability of the MI sensor, a test platform is set up and its performance, including the noise floor, the resolution, and the sensitivity, is comprehensively characterized. Furthermore, a comparative geomagnetic observation and magnetic anomaly detection among the proposed MI sensor, a high-precision Overhauser sensor, and a commonly used and accepted commercial MI sensor are conducted. The experimental results identify the capability of the proposed MI sensor in weak magnetic detection. [ABSTRACT FROM AUTHOR]

An Overhauser geomagnetic sensor is a precise instrument commonly employed for geomagnetic field observation, magnetic surveys, and so on. Currently, the miniaturization of the Overhauser geomagnetic sensor is limited due to the lower signal-to-noise ratio. Thus, how to effectively extract weaker free induction decay (FID) signal from a miniaturized sensor and how to improve the signal quality have become the bottleneck. To address these problems, we came up with an optimal design of the FID signal sensing coil for a miniaturized Overhauser geomagnetic sensor and propose a front-end matching circuit for the sensing coil to inhibit the attenuation of the signal amplitude caused by high impedance, further reducing the overall noise floor of the signal acquisition system. Finally, the field experimental results show that the miniaturized prototype sensor has a smaller volume and mass with an approximate performance compared with the commercial sensor. [ABSTRACT FROM AUTHOR]

In this Note, we develop a real-time magnetic field imaging system by employing a multi-magneto-inductive (MI) sensor array. The sensor array consists of 3 × 3 tri-axial MI sensors, which we constructed by using three sensor coils. Outputs from several rows of sensors are routed to a master-controller responsible for data pre-processing and data reconstruction. The data are streamed to a host computer via a universal serial bus interface, and the image can be generated and displayed at a rate of several frames per second. The magnetic field imaging is implemented on a knowledge of the MI sensors' response, magnetic field perturbations, and the nature of the ferromagnetic object respecting permeability and conductivity. The performance of the system has been further evaluated by extensive numerical modeling of magnetic field distribution patterns with partial differential equation solution. The proposed magnetic field imaging system can be employed in many potential applications, for instance, medicine, security screening, quality assurance, and other areas of nondestructive evaluation, designs associated with magnetic fields, teaching, and research. [ABSTRACT FROM AUTHOR]

The traditional aeromagnetic compensation model does not consider the negative effects of the gradient of the geomagnetic background field. Especially in emergency aeromagnetic surveys, this gradient effect is obvious and can reduce the performance of magnetic compensation. To solve this problem, we propose a method of reducing the gradient effect of the magnetic sensor for aeromagnetic compensation. A magnetic gradient model of the Earth's background field is established for the aeromagnetic compensation, and the gradient effect is then suppressed using altitude data. An experimental platform was built, and flight tests were conducted. Comparison results show that the adoption of the proposed method increased the improvement ratio (IR) of our compensator on two flights from 20.4 and 21.3 to 25.9 and 26.0, with the growth rates of the IR, respectively, reaching 27% and 22%. [ABSTRACT FROM AUTHOR]

In this Note, a new compressed sensing-based tuning algorithm has been developed to boost the sensor tuning performance of the proton precession magnetometers (PPMs). An end-to-end framework for the PPM's sensing free induction decay (FID) signal resonance based on orthogonal matching pursuit compressed sensing (OMPCS), dubbed OMPCS-FID resonance (OMPCS-FIDR), is developed and its working principle and implemented strategy are elaborated. By comparing the new sensor tuning approach with the state-of-the-art algorithms, i.e., peak detection, auto-correction, and secondary tuning, the results demonstrate that the proposed tuning method not only retains the performance but also overcomes the drawbacks of the state-of-the-art methods, which accelerates the possibilities of the PPM working in a scenario with a strong gradient magnetic field. [ABSTRACT FROM AUTHOR]

The proton precession magnetometer (PPM) is a commonly used device to measure the varying magnetic field. Since the frequency of the PPM sensing free induction decay (FID) signal is proportional to the magnetic field, the signal-to-noise ratio (SNR) is always a critical issue that influences the measurement accuracy severely due to the external interferences such as harmonic noise and random noise. In this study, to boost the SNR of the FID signal, an effective filtering algorithm based on time-frequency peak filtering (TFPF) analyzed with pseudo-Wigner–Ville distribution (PWVD) is proposed. Through pre-treating the collected noisy FID signal with frequency modulation and instantaneous frequency estimation using the peak value of the time-frequency characterization, the embedded noise can be decorrelated and the relative pure FID signal can be detected regardless of the impact of varying noise levels. The superiority of the proposed synaptic noise reduction framework, namely, TFPF-PWVD, was found by comparing it with state-of-the-art approaches under the same conditions. The results illustrated that even though in a strong-noisy scenario, the proposed TFPF-PWVD based approach still achieved the best SNR for the yielded sensing FID and the minimum standard deviation for the observed magnetic field data, which can enhance the geomagnetic measuring performance of a PPM. [ABSTRACT FROM AUTHOR]

Concealed metallic object detection is one of the critical tasks for any security system. It has been proved that different objects have their own magnetic fingerprints, which are a series of magnetic anomalies determined by shape, size, physical composition, etc. This study addresses the design of a low-cost power security system for the detection of metallic objects according to their response to the magnetic field. The system consists of three anisotropic magnetoresistance (AMR) sensor arrays, detection circuits, and a microcontroller. A magnetic gradient full-tensor configuration, utilizing four AMR sensors arranged on a planar cross structure, was employed to construct a two-dimensional image from the obtained data, which can further suppress the background noise and reduce the orientation and orthogonality errors. The performance of the system is validated by data validation and multiple object feature segmentation. Numerous magnetic fingerprinting results demonstrate that the system can configure metallic objects more than 50cm clearly and identify multiple objects separated by less than 20 cm, which indicates the feasibility of using this magnetic gradient tensor fingerprint method for metallic object detection. [ABSTRACT FROM AUTHOR]

A magnetic sensor of the optically pumped magnetometer may enter a dead zone during an aeromagnetic survey, resulting in unavoidable abnormal data and seriously affecting the effect of aeromagnetic compensation. We propose a fast discrimination and culling method based on the Hough transform to prevent abnormal data from participating in the coefficient estimation. In the proposed method, the parameter space is partitioned into small buckets and the most frequently passed region of sinusoidal curves is detected to eliminate abnormal data. Although the conventional method performs similarly to the proposed method when there is only 1% abnormal data, it is theoretically shown that the proposed method has a better goodness of fit of 0.9518, compared with a value of 0.1956 for the conventional method, in the presence of 45% abnormal data. Furthermore, we construct an experimental platform and conduct a flight test in which the proposed method has an improvement ratio of 4.11 compared with a value of 0.34 for the conventional method. [ABSTRACT FROM AUTHOR]

The free induction decay (FID) transversal signal is always employed by a proton precession magnetometer (PPM) to evaluate the time-domain geomagnetic field. Nevertheless, the signal-to-noise ratio (SNR) is an important factor that severely affects the detection accuracy of the magnetic field due to uncontrollable interference sources, including random noise and power frequency noise. In this study, aiming to boost the SNR of the FID transversal signal, a novel filtering algorithm based on a prewhiten (PW) strategy is proposed and the PW filtering was combined with singular value decomposition (SVD) for further noise reduction. This method aims to generate adaptive PW input data before filtering, further decorrelating the noise to reduce the impact of varying noise levels in the received FID signals. The efficiency of the proposed joint filtering framework, dubbed PW-SVD, was evaluated by comparing with two state-of-the-art methods, i.e., SVD and principal component analysis and decomposition, using the same data. The results demonstrated that the proposed PW-SVD method obtained the smallest root mean square error and the highest signal-to-noise ratio improvement among all the compared methods, especially for the strong-noisy scenario, which enhances the environmental adaptability of a PPM. [ABSTRACT FROM AUTHOR]

The free induction decay (FID) transversal data determines the measurement accuracy of time-dependent geomagnetic fields, whereas the conservation of clean components and removal of noise cannot be easily achieved for this kind of data. Even though numerous techniques have been proven to be effective in improving the signal-to-noise ratio by filtering out frequency bands, how to efficiently reduce noise is still a crucial issue due to several restrictions, e.g., prior information requirement, stationary data assumption. To end this, a new multivariate algorithm based on the fusion of principal component analysis (PCA) and singular value decomposition (SVD), namely, principal component analysis and decomposition (PCAD), was presented. This novel algorithm aims to reduce noise as well as cancel the interference of FID transversal data. Specifically, the PCAD algorithm is able to obtain the dominant principal components of the FID and that of the noise floor by PCA, in which an optimal number of subspaces could be retained via a cumulative percent of variance criterion. Furthermore, the PCA was combined with an SVD filter whose singular values corresponding to the interferences were identified, and then the noise was suppressed by nulling the corresponding singular values, which was able to achieve an optimum trade-off between the preservation of pure FID data and the denoising efficiency. Our proposed PCAD algorithm was compared with the widely used filter methods via extensive experiments on synthetic and real FID transversal data under different noise levels. The results demonstrated that this method can preserve the FID transversal data better and shows a significant improvement in noise suppression. [ABSTRACT FROM AUTHOR]

The polarization frequency of free radical solution in Overhauser geomagnetic sensor determines the quality of the Larmor precession signal generated by the sensor. To obtain the polarization frequency accurately, a test apparatus was designed in this paper, which can overcome existing problems in the presently used apparatuses, such as lower resolution, complex operation, etc. The proposed apparatus adopts a high-resolution direct digital synthesis as the controllable radio frequency (RF) signal source. Meanwhile, an analog-to-digital converter synchronization acquisition technology combined with a normalization approach is proposed, which effectively solves the problem of the uneven amplitude-frequency characteristic in the range of 50 MHz–100 MHz. Moreover, the apparatus is integrated by adopting the RF power and applying the weak signal amplifier as an auxiliary measurement channel. The equivalent circuit of the sensors resonant cavity was simulated, and the efficiency curve of the adjustable capacitors to the resonant frequency and the quality factor were obtained. The simulated results were further verified by testing the resonance cavity characteristics of a commercial Overhauser geomagnetic sensor under different conditions. Furthermore, the relationship between the polarization degree of the free radical solution and RF excitation power and time were also obtained. The testing methods and results were given, and the experimental data were analyzed. Finally, the experimental results demonstrate that the proposed apparatus can measure the polarization frequency of the free radical solution, the bandwidth, and the quality factor, accurately. Furthermore, it can be used for the determination of the polarization power and time during the design process for an Overhauser magnetometer. [ABSTRACT FROM AUTHOR]

Improving the precision and sampling rate of the resonance frequency of cesium atoms is the key to enhancing the same factors of an airborne optically pumped cesium magnetometer (AOPCM). Aiming at the existed problems of AOPCM and characteristics of resonance signal, this paper proposes a high-precision and fast-sampling frequency measurement method based on carry chains of Field-Programmable Gate Array (FPGA). In order to achieve a fast-sampling rate, an improved equal precision frequency measurement method is proposed to measure the standard signal and the resonance signal continuously. Besides, by using the serial full adder to connect FPGA carry chains to a delay line, the delay line is used to compensate the unsynchronized clock edge, so the counting error can be reduced, and the precision of frequency measurement can be improved greatly. Experiments show that the frequency resolution is 0.014 nT and the relative error is lower than 2 × 10−6 when the sampling rate is 500 Hz. The experimental result indicates that the proposed method improves the precision and sampling rate of resonance frequency measurement greatly. Consequently, the precision and sampling rate of AOPCM can be improved. [ABSTRACT FROM AUTHOR]