Boris Ginzburg

Magnetic Anomaly Detection Using a Three-Axis Magnetometer

Magnetic anomaly detection is a good method for detecting ferromagnetic objects, particularly hidden targets. In this work, we address the detection of a moving ferromagnetic target using a static three-axis referenced magnetometer. The analysis and the results are also applicable to the converse case of a static ferromagnetic target and a moving three-axis referenced magnetometer. We use the three magnetometer outputs to build a total magnetic field of the target. This signal is decomposed into a set of orthonormal basis functions, out of which the dominant basis function is chosen as the detector. The detector provides output responses to any target magnetic moment orientation. We support the analysis by a computer simulation and real-world experimental results. The high detection probability and the simple implementation of the proposed method make it attractive for real-time applications.

Processing of magnetic scalar gradiometer signals using orthonormalized functions

This work relates to the detection of hidden ferromagnetic objects with the use of a gradiometer that comprises two scalar sensors and functions as a magnetic anomaly detector (MAD). A hidden object is represented by a magnetostatic dipole. Modeling of the MAD output signal is carried out by its decomposition in the space of orthogonal functions (an orthonormal basis) constructed with the use of Gram-Schmidt algorithm. A set of five functions is found to be sufficient for an accurate signal description in a wide range of distances between the gradiometer and the dipole. The dipole energy signal is introduced in the basis chosen and is found to be a useful function for the data processing algorithm based upon the results of the modeling. It is shown that the use of this function improves either the signal-to-noise ratio or the detection characteristics. Moreover, the dipole energy signal turns out to be independent of the dipole orientation. This leads to the possibility of using an identical signal processing algorithm for all variety of dipole waveforms.

Localization and magnetic moment estimation of a ferromagnetic target by simulated annealing

In many applications, the detection of a visually obscured magnetic target is followed by the characterization of the target, i.e. localization and magnetic moment estimation. Effective target characterization may reduce the detection false alarm rate as well as direct the searcher toward the target. We address the characterization of a static magnetic target by a three-axis fluxgate magnetometer installed on a stabilized mobile platform. The magnetometer readings are contaminated by magnetic noise, which results in a low signal-to-noise ratio. We formulate the problem as an over-determined nonlinear equation set using a magnetic dipole model for the target and use simulated annealing (SA) in order to rapidly find a good approximation to the global optimum of this equation set. Computer simulations demonstrate high accuracy of the SA method in localizing the target and estimating its magnetic moment in the presence of high-level noise. The high accuracy of the SA method is also exemplified in tests employing real-world magnetic signals. In addition to its high accuracy, the SA method is very rapid, making it appropriate for real-time practical applications.

Magnetic Anomaly Detection Using High-Order Crossing Method

Magnetic anomaly detection (MAD) is a passive method used to detect visually obscured ferromagnetic objects by revealing the anomalies in the ambient Earth magnetic field. In this paper, we propose a method for MAD employing the high-order crossing (HOC) approach, which relies on the magnetic background nature. HOC is an alternative method for spectral analysis using zero-crossing count, also enabling signal discrimination. Tests with real-world recorded magnetic signals show high detection probability even for low signal-to-noise ratio. The high detection probability, together with a simple implementation and low power consumption, makes the HOC method attractive for real-time MAD applications such as intruder detection and for research on an earthquake magnetic precursor.

Magnetic anomaly detection using entropy filter

We address the detection of a ferromagnetic target that generates an anomaly in the ambient Earth magnetic field. Detection of an anomaly buried in magnetic noise requires the use of a magnetic anomaly detector (MAD), such as the orthonormal basis functions (OBFs) detector. In contrast to the OBFs detector that relies on target signal waveform ensemble, we propose the adaptive minimum entropy detector (MED) to detect any changes in the magnetic noise pattern. Hence, we have constructed the MED based on the magnetic noise probability density function. The MED was tested on real-world magnetic noise and compared to the OBFs detector. Higher detection rate was exemplified for the MED over the OBFs detector in detecting a ferromagnetic target with low signal-to-noise ratio (SNR). Appreciable advantage of the MED over the OBFs detector is shown, when the target does not move according to the assumed pattern. The low-computational complexity makes the MED appropriate for real time applications.

Localization in 2D Using Beacons of Low Frequency Magnetic Field

In this work we propose methods for object localization in 2D using beacons of low frequency quasi-static magnetic field. From a practical point of view, localization in 2D is sufficient for many applications, requiring much less calculations than in 3D, making it more robust and easier to implement in real-time low power applications. The low frequency magnetic field may penetrate foliage, soil, buildings, and many other types of media. This is an important advantage over traditional localization methods such as sonar or radar, where effective operation requires line-of-sight. Another advantage of the low frequency magnetic fields is that there is no direct influence by bad weather conditions and diurnal variations. Opposite to traditional electromagnetic methods, where operational range is usually more than a wavelength, low frequency induction approach results in a relatively limited localization range. Each beacon comprises a coil generating a magnetic field of a unique frequency in the ULF band. The generated magnetic fields are sensed by a search-coil magnetometer. The magnetometer readings are processed to estimate the magnitude and phase of the received beacons signals, which are used to localize the magnetometer. For a moving object, we propose to combine localization together with tracking algorithm using a data fusion approach. The proposed methods have been tested using numerous computer simulations, showing accurate localization results. A prototype was developed and used in field experiments, validating simulation results. The good accuracy together with a simple implementation makes the proposed methods attractive to many real-time low power field applications.

High Resolution Marine Magnetic Survey of Shallow Water Littoral Area

The purpose of this paper is to present a system developed for detection and accurate mapping of ferro-metallic objects buried below the seabed in shallow waters. The system comprises a precise magnetic gradiometer and navigation subsystem, both installed on a non-magnetic catamaran towed by a low-magnetic interfering boat. In addition we present the results of a marine survey of a near-shore area in the vicinity of Atlit, a town situated on the Mediterranean coast of Israel, about 15 km south of Haifa. The primary purpose of the survey was to search for a Harvard airplane that crashed into the sea in 1960. A magnetic map of the survey area (3.5 km2 on a 0.5 m grid) was created revealing the anomalies at sub-meter accuracy. For each investigated target location a corresponding ferro-metallic item was dug out, one of which turned to be very similar to a part of the crashed airplane. The accuracy of location was confirmed by matching the position of the actual dug artifacts with the magnetic map within a range of ± 1 m, in a water depth of 9 m.

Aeromagnetic Search Using Genetic Algorithm

We propose the Genetic Algorithm (GA) approach for localization of an underwater magnetic dipole target by an airborne magnetometer. Airborne Magnetic Anomaly Detection (MAD) is used for decades to detect underwater targets, such as sunken ships. The target is assumed as a magnetic dipole, which produces an anomaly in the dominant Earth magnetic field. The aircraft follows a path, sampling the magnetic field and utilizing GA to estimate target location and magnetic moment. The method was simulated on a personal computer, obtaining promising results in the presence of noise. A scatter radius of about 60 m is achieved for SNR value of 0.2, which is acceptable for practical needs.