Suppression of interference in threat detection

Abstract

The method includes receiving data characterizing signals acquired by a plurality of magnetic field receivers, the signals being formed from a combination of a first magnetic field, a second magnetic field resulting from an interaction of the first magnetic field with the first object, and a third signal resulting from a movement of the receiver within the first magnetic field and / or within an external magnetic field other than the first magnetic field. The method also includes determining a component of the signal characterizing a contribution of the second magnetic field to the signal, the determining component including at least multiplying the received data by a mapping characterizing a contribution of the third signal to the signal to cancel the contribution of the third signal. The method further includes providing the determined component of the signal characterizing the contribution of the second magnetic field to the signal. Related systems and computer program products are also provided.

Description

[Technical field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority under 35 U.S.C. § 119(e) to U.S. Provisional Application No. 63 / 238,849, filed August 31, 2021, and entitled “Suppression of Interference in Threat Detection,” the entire contents of which are incorporated herein by reference.

[0002] Technical Field The subject matter described herein relates to personnel screening systems and, in some example embodiments, to personnel screening systems that can perform threat detection and discrimination without confiscating personal items. [Background technology]

[0003] Airport security attempts to prevent any threatening or potentially dangerous situations from occurring or entering the country. Some existing radio frequency (RF) imaging systems (such as those utilized by airport security for passenger screening) are large, expensive, and require the individual to remain stationary while an antenna rotates around the individual to capture an image. Additionally, these existing RF imaging systems may require confiscation of personal items such as cellular phones, keys, wallets, etc. by the individual being screened. The need for such confiscation may reduce the throughput and usefulness of the imaging system. Summary of the Invention [Problem to be solved by the invention]

[0004] Some existing inspection systems, such as walk-through metal detectors, may include coils for generating and measuring changes in a magnetic field caused by a magnetic or conductive material (e.g., metal) passing through the field. While these existing inspection systems may measure metal objects passing through the boundary, they may lack the ability to distinguish personal items such as cellular phones, laptops, keys, belt buckles, etc. from threats such as firearms or improvised explosive devices. Thus, these exemplary existing inspection systems require confiscation of personal items, thereby limiting their throughput and usefulness. [Means for solving the problem]

[0005] Various aspects of the disclosed subject matter may provide one or more of the following features.

[0006] In some embodiments, the method includes receiving data characterizing signals acquired by a plurality of magnetic field receivers, the signals being formed from a combination of a first magnetic field, a second magnetic field resulting from an interaction of the first magnetic field with the first object, and a third signal resulting from a movement of the receiver within the first magnetic field and / or within an external magnetic field other than the first magnetic field. The external magnetic field is generated by an external source. The method also includes determining a component of the signal characterizing a contribution of the second magnetic field to the signal. Determining the component includes at least multiplying the received data by a mapping characterizing a contribution of the third signal to the signal to cancel the contribution of the third signal. The method further includes providing the determined component of the signal characterizing the contribution of the second magnetic field to the signal.

[0007] One or more of the following features may be included in any possible combination.

[0008] In some embodiments, the determining includes transforming the received data characterizing the signal from a first basis to a second basis. The determining also includes modifying the transformed data by at least canceling a portion of the transformed data that corresponds to a projection of the transformed data on predetermined basis vectors indicative of a magnetic field generated by the second object to generate modified data. The determining further includes transforming the modified data from the second basis to the first basis.

[0009] In some embodiments, the method further includes calculating a first matrix indicative of a magnetic field measurement associated with a magnetic field generated by an external source in the absence of the first magnetic field, and performing a singular value decomposition on the first matrix to generate a second matrix including a plurality of left singular vectors of the first matrix and a third matrix including singular values ​​associated with the first matrix in its diagonal components.

[0010] In some embodiments, converting the received data from the first basis to the second basis includes multiplying the received data by a second matrix. In some embodiments, the method further includes generating a fourth matrix by at least setting a first singular value in a diagonal element of the third matrix that is greater than or equal to a predetermined value to zero and setting a second singular value in a diagonal element of the third matrix that is less than the predetermined value to one. A first left singular vector of the plurality of left singular vectors is associated with the first singular value, and the predetermined basis vectors indicative of the magnetic field generated by the second object include the first left singular vector.

[0011] In some embodiments, modifying the transformed data includes multiplying a result of the multiplication between the received data and the second matrix by a fourth matrix. In some embodiments, converting the modified data from the second basis to the first basis includes multiplying the modified data by a transpose of the second matrix. In some embodiments, the method further includes calculating a polarizability of the target object from the determined component of the signal characterizing a contribution of the second magnetic field to the signal. The polarizability characterizes a magnetic polarization property of the target object.

[0012] In some embodiments, the method further includes calculating a fifth matrix indicative of magnetic field measurements resulting from a rotation of one or more of the plurality of magnetic field receivers about a predetermined axis. A matrix element of the fifth matrix associated with a first magnetic field receiver is calculated by multiplying an angular displacement of the first magnetic field receiver by at least a predetermined expansion of a mode of the first magnetic field receiver associated with the angular displacement. In some embodiments, the first object is a target object being inspected and the second object is a stationary interfering object.

[0013] Details of one or more variations of the subject matter described herein are set forth in the accompanying drawings and the following detailed description. Other features and advantages of the subject matter described herein will become apparent from the detailed description and drawings, and from the claims. [Brief description of the drawings]

[0014] [Figure 1] FIG. 1 is a system block diagram of an example inspection system that can perform threat detection in the presence of external interference. [Diagram 2] FIG. 2 is a processing block diagram illustrating an example process of an example inspection system in accordance with some aspects of the present subject matter. [Diagram 3] 1 illustrates an example spatial and temporal interference from an interference source associated with an interfering system. [Figure 4] FIG. 2 shows an example interference signal (left) and an example measurement signal (right). [Diagram 5] FIG. 5 shows a superposed signal generated by superposing the interference signal and the measurement signal of FIG. 4 (left side) and the transformed superposed signal (right side). [Figure 6] 6 shows an exemplary modified signal (left) calculated by canceling a portion of an interference signal from the transformed superimposed signal of FIG. 5 and a second transformed signal (right) calculated by transforming the modified signal. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] Like reference symbols in the various drawings indicate like elements.

[0016] Inspection systems based on magnetic field detection can be used to detect target objects (e.g., objects that represent potential threats). Such inspection systems may be deployed in environments (e.g., courthouses, airports, etc.) that may include objects that may interfere with the detection of the target object. These objects, sometimes referred to as interfering objects, may generate interfering signals that may obscure signals from the target object. For example, the target object may generate a target magnetic field signal in response to a primary magnetic field generated by the inspection system, which may be detected by the inspection system. The interfering magnetic field may be generated by the interfering object (e.g., by a current carrying object that generates a magnetic field independent of the inspection system) and may be detected by the inspection system. The interfering magnetic field may interfere with the detection of the target object by the inspection system. Some embodiments of the present subject matter may enable suppression of the interfering signals from the interfering objects, resulting in improved identification of the target object.

[0017] In some embodiments, suppressing the interfering signal may include performing magnetic field measurements of the environment of the inspection system, including the interfering object, in the absence of a magnetic field from the inspection system. These measurements may be referred to as dark measurements because they are taken when the inspection system is not transmitting a magnetic field. Data collected from the dark measurements may be analyzed (e.g., using singular value decomposition) and stored.

[0018] Inspection systems based on magnetic field detection may also be subject to apparent magnetic field disturbances caused by motion of the transmitter and / or receiver of the inspection system. This motion may generate interference signals that may obscure signals from a target object. In some embodiments, suppressing interference signals caused by motion may include performing or simulating magnetic field measurements while the transmitter and / or receiver of the system are moving. Data collected or simulated during this motion may be analyzed (e.g., using singular value decomposition) and stored.

[0019] An inspection algorithm of the inspection system may be modified (e.g., prior to inspection of the target object) based on the dark measurement data and / or the motion measurement data and stored. During inspection of the target object, a signal from the target object may be transformed based on the dark measurement data and / or the motion measurement data, and a property of the target object (e.g., the polarizability of the target object) may be retrieved using the modified inspection algorithm.

[0020] An exemplary inspection system will now be described. FIG. 1 is a system block diagram of an exemplary inspection system 100 that can suppress (e.g., remove) external interference that may affect the detection of the inspection system 100. As shown in FIG. 1, the system 100 includes multiple magnetic receivers 105 connected to a data acquisition base station 115. The data acquisition base station 115 may be configured to filter, demodulate, and digitize magnetic field measurement data received from the receivers 105. The multiple transmitters 106 and multiple magnetic receivers 105 may be positioned to survey an observational domain (OD) 107, sometimes referred to as a "scene," such as a boundary or other defined area. The OD may include a target object 168 and multiple putative sources 170a-c. One or more of the interference sources 170a-c may interfere with the inspection of the target object 168 (e.g., by ob). The interference sources (e.g., electronic devices, power lines, etc.) may, for example, obscure signals from the target object 168.

[0021] The OD 107 may be considered to include voxels that define a volume. The OD 107 may be a single contiguous region or multiple distinct regions. The system 100 also includes multiple transmitters 106 connected to a transmit driver 160. The transmit driver 160 may be configured to generate signals to drive the transmitters 106. The system 100 further includes a processing system 120 configured to analyze the received magnetic field measurements. The processing system 120 includes a data acquisition module 130, a calibration module 135, a reconstruction module 140, an automated threat recognition module 145, a rendering module 150, and a memory 155. The system 100 may also include a display 165 that provides an output, and a sensor 125 that provides additional input to the system 100.

[0022] In some embodiments, the system may be configured to operate as a distributed lock-in amplifier that uses a synchronous homodyne digital dual-phase demodulation technique to accurately extract in-phase (I) and quadrature (Q) information from the system's particular transmission frequency. Demodulation may be accomplished by digitally mixing or multiplying the desired signal with a reference signal and then filtering the result with a low-pass filter. The reference signal may be a directly measured signal related to or derived from the drive signal used in the transmitter, or it may be a synthetic analog signal. By utilizing two versions of the reference signal, one phase-shifted or time-delayed with respect to the other, the amplitude, phase, and / or I and Q of the measurement signal may be reconstructed.

[0023] In some embodiments, the transmit driver 160 may include a combination of a digitally controlled high precision direct digital synthesis (DDS) waveform generator, a digitally controlled sum programmable-gain amplifier (PGA) circuit, and a closed-loop class D power amplifier with improved power supply rejection ratio (PSRR). Such a system provides flexibility in the frequency and amplitude of the transmit waveform while achieving high stability in the transmit magnetic field required to meet the required signal-to-noise ratio in the measurement data. The system 100 may digitally control the amplitude and frequency of the transmit magnetic field. Digitally controlling the amplitude and frequency of the transmit magnetic field may be performed in a dynamic manner or in any ad-hoc manner. In some embodiments, the system may include a closed-loop microcontroller-based feedback system configured to measure and dynamically adjust the amplitude per frequency of the transmit magnetic field, thereby improving the stability and predictability of the system.

[0024] The transmitter 106 may include at least two wire loop transmitters capable of generating a magnetic field according to a drive signal having a predetermined operating (e.g., characteristic) frequency (e.g., modulation frequency). The transmitter 106 may operate, for example, at 30 Hz and 130 Hz. In general, the wire loop may be considered to be in a predetermined major plane. In some embodiments, the system 100 may include multiple transmitters arranged to generate magnetic fields with sufficient diversity to interrogate all major directions (e.g., Cartesian coordinates) throughout the OD 107. In a stationary frame in which the object under inspection is stationary, the system may include at least three transmitters that are orthogonally oriented (e.g., the major planes of each of the three transmitters may be orthogonally oriented) or spatially offset from one another. If the object is experiencing motion in a particular direction, such as an object passing through the inspection system 100, two transmitters may be used, provided that each transmitter is orthogonal to the direction of motion or spatially offset across both the direction of motion and their shared orientation. This configuration represents a reasonable constraint on object motion (e.g., in one direction) and may also represent the minimum number of transmitter coils that can provide sufficient magnetic field diversity to interrogate a given object.

[0025] As shown in FIG. 1, the transmitter driver 160 may generate one or more signals to drive the transmitters 106. In some embodiments, the multiple transmitters 106 may be driven by cycling through the multiple transmitters one by one in time until all desired measurements have been taken. Advantages of such an approach may include the ability to share drive electronics across all transmitters 106. However, this approach imposes a predefined duty cycle on each transmitter 106, which may reduce its signal-to-noise ratio. In such a configuration, the multiple transmitters 106 may not be measured at the same instant, which may introduce motion artifacts if the object is moving.

[0026] In some embodiments, multiple transmitters 106 may be driven simultaneously but at slightly (e.g., 10 Hertz (Hz)) offset frequencies. The multiple frequencies may be offset enough to allow them to be clearly demodulated in post-processing, which may be set by the bandwidth required to characterize the object's motion with a given resolution, which may be about 5-10 Hz for an object moving at a typical walking speed of 1.3 meters per second (m / s). At the same time, the multiple frequencies may be selected similar enough to allow negligible dispersion in polarizability. In some embodiments, the offset may be 10 Hz, which is a negligible difference at all and can be considered to be a vanishing frequency. In this exemplary frequency multiplexing approach, the transmit driver 160 may include separate drive electronics to drive each transmitter separately, which may allow for improved signal-to-noise ratio without (and / or with reduced risk of) motion blur.

[0027] In some embodiments, the transmit driver 160 may be capable of generating multiple drive signals that can be distributed to multiple transmitters 106, which can establish a fully phase coherent measurement system across all receive-transmit pairs. Additionally, the drive signals may be provided as reference signals routed from the transmitter driver 160 to the data acquisition base station 115, which can be used for demodulation, as described in more detail below.

[0028] The magnetic receivers 105 may include fluxgate sensors, which can directly measure the magnetic field (e.g., magnitude and phase) as compared to wire coils, which measure the rate of change of the magnetic field. In some embodiments, one or more of the receivers 105 may include a three-axis fluxgate magnetometer. In some embodiments, one or more of the receivers 105 may include a two-axis fluxgate magnetometer. Fluxgate magnetometers can be advantageous in that they can operate with high sensitivity, high linearity, and a low noise floor as compared to coil receivers. The receivers 105 can make accurate magnetic measurements at frequencies too low for conventional methods.

[0029] The fluxgate sensor may measure the amplitude of the magnetic field in three axes (e.g., x, y, and z) at the location of the fluxgate sensor. The fluxgate sensor may include a sense coil surrounding an inner drive coil wound closely around a core material having high magnetic permeability, such as mu-metal. An alternating current may be applied to the drive winding, which drives the core in a continuous repeating cycle of saturation and desaturation. With the core in a state of high magnetic permeability in the presence of an external magnetic field, such a magnetic field is attracted or gated locally through the sense winding. Continuously gating the external magnetic field into and out of the sense winding induces a signal in the sense winding, the dominant frequency of which is twice the drive frequency, and the magnitude and phase orientation of which vary directly proportional to the magnitude and polarity of the external magnetic field.

[0030] In some embodiments, fluxgate sensors may be utilized with operating frequencies below 1 kHz, such as 130 Hz and 30 Hz. At these relatively low operating frequencies, fluxgate sensors can operate with an improved noise floor, for example, some fluxgates can achieve voltage to magnetic field ratios on the order of 20 microvolts / nanotesla.

[0031] The data acquisition base station 115 may demodulate, filter, and digitize data received from the receiver 105. The data acquisition base station 115 may aggregate the received data, determine in-phase and quadrature data (I and Q data, respectively) from the received aggregated digitized data, and transmit the aggregated data as in-phase and quadrature data to the processing system 120. Filtering and amplifying the raw magnetometer signals provided to the data acquisition module 130 enables the system to achieve high dynamic range at frequencies of interest, e.g., frequencies below 1 kHz, such as 130 Hz and 30 Hz, by rejecting large direct current (DC) magnetic signals in the environment. The bandwidth and design of the filters used in the hardware and / or software of the system 100 may be selected to reject undesired signals in the environment, such as 50 and 60 Hz signals generated by alternating current (AC) lines, while retaining sufficient bandwidth in the demodulated signal to recover the motion of the object.

[0032] The sensor 125 may include an infrared (IR) camera, a thermal camera, an ultrasonic distance sensor, a video camera, an electro-optical (EO) camera, and / or a surface / depth map camera. The sensor 125 generates additional information images or videos, such as optical images, of at least the OD 107. In some embodiments, the sensor 125 transmits the images or videos to the processing system 120 for further analysis. The system 100 may include multiple sensors 125. The sensor 125 may be used to detect the presence of a target at the OD 107. Detecting the presence of a target at the OD 107 may be used to trigger a scan by the system 100. In some embodiments, the sensor 125 may include a radio frequency identification (RFID) reader.

[0033] The system may also present images to the operator via a display 165, where the visible portions of the visitor and / or their appendages that are most likely to contain one or more objects are highlighted, segmented, or otherwise provided with a notification to the operator to aid in the operator's response. Additionally, the aspect of the object may be determined based on the image obtained from the depth camera. The acquired aspect may be associated with a classification of the object. For example, if the object has a flat appearance, the magnetic detection algorithm may determine the class of the object, such as determining that the object is a laptop or an umbrella. If the object is concealed, the magnetic detection algorithm may determine the part or location of the human body where the object is concealed, such as a pocket of the person's clothing, the person's ankle or wrist, or a bag that the person may be carrying. Data associated with these locations may be combined with information derived from the magnetic field data in a classification step, where the classification step uses all available information to achieve greater predictive accuracy during threat detection.

[0034] The processing system 120 includes a number of modules for processing the magnetic field data and additional information images from the sensor 125 of the OD 107, including a data acquisition module 130, a calibration module 135, a reconstruction module 140, an automatic threat recognition module 145, a rendering module 150, and a memory 155.

[0035] The data acquisition module 130 acquires a time series of voltage measurements representing magnetic field measurements from the DAS base station 115 and additional information images from the sensor 125. In some embodiments, the sampling rate of the data acquisition module 130 is derived from the same master clock used to generate the transmitted magnetic field via the transmitter 106. For each receiver 105, the data acquisition module 130 performs demodulation with an associated reference signal in post-processing to derive I and Q data from this time series. The timing of the I and Q data may be synchronized across multiple receivers 105, and the data acquisition module 130 may issue the synchronized data as multiple frames (e.g., time slices) for further analysis by the system 100.

[0036] In some embodiments, the master clock of the system 100 may be distributed over several meters of space in the system using a low jitter and low distortion clock fanout and an internal network of low voltage differential signaling (LVDS) converters. This configuration allows the sampling rate to be an integer harmonic of all transmitted frequencies, eliminating digitization errors that may impair the sensitivity of the system. By configuring each device in the data acquisition process 130 in the same clock domain, the receivers 105 can be located several meters apart from each other and can be correctly assumed to be receiving samples at the same time intervals without drift due to frequency mismatch. Thus, for a given frame, the data acquisition module 130 issues a set of data for each receiver 105 and sensor 125. In some embodiments, data may be acquired, and frames issued, at a rate sufficient to identify the carrier frequency to a predetermined resolution.

[0037] In some embodiments, the data acquisition module 130 removes static background signals (e.g., the primary magnetic field). In some embodiments, the data acquisition base station 115 may remove static background signals (e.g., the primary magnetic field) such that the I and Q data characterize the secondary magnetic field rather than the primary magnetic field.

[0038] The calibration module 135 applies calibration corrections to the emitted data. The calibration corrections may include compensating the emitted data for serial time sampling. Additionally, the calibration module 135 may compare the measured primary magnetic field to one or more magnetic field model predictions and compensate for any differences. In some embodiments, the calibration may account for transmitter amplitude and phase changes that occur due to normal wear and tear, manufacturing variations, or temperature changes.

[0039] The reconstruction module 140 converts the calibrated data into images and / or feature maps. Images may be generated for each receiver 105 and / or may be generated based on a composite of measurements taken by multiple receivers 105. The reconstruction module 140 may include determining polarizability measurements (e.g., tensors) and localization of the object.

[0040] The polarizability may be characterized as a proportionality constant relating the far-field response of an object to the primary magnetic field that induced it. It may have units of volume and may depend on the frequency of the applied magnetic field, as well as on the shape, permeability, and conductivity of the object. To determine the polarizability, in some embodiments, a best-fit algorithm may be utilized to implement a minimum residual matched filter.

[0041] The transmitter magnetic field may be calculated from a rectangular coil model, and the receiver magnetic field may be calculated from the dipole magnetic field along a particular axis of the sensor, such that a three-axis receiver node is treated as three independent and orthogonal dipoles.

[0042] In some embodiments, image data from sensor 125 may be used to further enforce sparseness constraints beyond those provided by a priori knowledge of objects or entities that may occupy OD 107. Specifically, images of OD 107 acquired by sensor 125 may be used to determine the spatial location of targets (e.g., in which voxels of OD 107 targets reside and which voxels of OD 107 are empty). Empty voxels do not contain objects and may therefore be considered zero for compressed detection (e.g., allowing for better and / or faster estimation of solutions to underdetermined linear systems).

[0043] Furthermore, an OD 107 with an appropriate size may result in a scene that is sparse enough for compressed detection. For example, if the OD 107 has a volume of 2 meters by 1 meter by 0.5 meters and is divided into 8,000,000 5 mm voxels, a typical human located inside the OD 107 would only occupy about 10% of the voxels (e.g., about 800,000 voxels) at any given moment. The set of retrieved polarizable objects from the sensor 125 may be used to determine a three-dimensional surface inside the volume of the OD 107 and thus determine in which voxels an individual is present. Empty voxels may be forced to zero when searching for the set of polarizable objects, while voxels with non-zero values ​​may be changed during reconstruction (e.g., may be considered as variables to find a reconstructed optimal solution of an underdetermined linear system).

[0044] The reconstruction module 140 may reconstruct one or more magnetically searched sets of polarizable objects. Additionally, the reconstruction module 140 may combine multiple independent searched sets of polarizable objects to generate a searched and aggregated set of polarizable objects. In some embodiments, the reconstruction module 140 may treat all receivers 105 as one large sparse aperture and reconstruct a single searched set of polarizable objects using information obtained from all receivers 105 in this single aperture.

[0045] The reconstruction module 140 may perform localization of the object using multiple time slices. Such an approach may use a single model fitting approach that solves for the location (e.g., x, y, and t-crossings), velocity, and polarizability tensors for the object. Exemplary localization approaches are described in more detail below.

[0046] The reconstruction module 140 may generate a feature map from the reconstructed images. The feature map may include characterizations or features of the magnetic measurements. Statistical analysis may be performed across multiple images. Some exemplary features include magnetic field magnitude, magnetic field phase, and polarizability tensor properties (discussed in more detail below). Other features are also possible.

[0047] The automated threat recognition module 145 analyzes the images and / or feature maps for the presence or absence of threat objects. Threat objects may include dangerous items that an individual may be carrying or concealing, such as firearms and explosives. The automated threat recognition module 145 may identify threats, for example, using a classifier that evaluates the feature map generated by the reconstruction module 140. The classifier may be trained based on known threat characteristics. In some embodiments, the threat recognition process may compare the determined images against a library of pre-defined polarizability signatures.

[0048] In some embodiments, the features (eg, classification variables) may include magnetic field magnitude, phase, and polarizability tensor properties at one or more operating frequencies.

[0049] The rendering module 150 generates or renders an image characterizing the results of the threat recognition analysis performed by the threat recognition module 145. The image may be rendered on the display 165. For example, the rendering module 150 may display an avatar of the person scanned and any identified threats. The rendering module 150 may display characteristic values ​​where the automated threat recognition module 145 did not detect any threats.

[0050] 2 is a flow chart illustrating an exemplary method of suppressing external interference. In step 202, data may be received characterizing signals acquired by multiple magnetic field receivers (e.g., magnetic receivers 105). The signals may represent a combination of a first magnetic field (e.g., generated by transmitter 106), a second magnetic field resulting from the interaction of the first magnetic field and a first object (e.g., target object 168 or a portion thereof), and a third magnetic signal resulting from interference (e.g., one or more of interfering object or sensor motions 170a-c). For example, the third signal may be caused by (or represent) a motion of the receiver within the first magnetic field and / or within an external magnetic field (e.g., different from the first magnetic field) that may be generated by an external source.

[0051] In step 204, a component of the signal characterizing the contribution of the second magnetic field (or the target magnetic field from the target object 168) to the signal may be determined. Determining the component may include at least multiplying the received data by a mapping characterizing the contribution of a third magnetic field (or an interfering magnetic field from one or more interfering objects 170a-c) to the signal to cancel the contribution of the third magnetic field.

[0052] In some embodiments, the determining may be based on dark measurements by the magnetic receiver 105, which may include performing magnetic field measurements of the environment of the inspection system, including the interfering object, in the absence of the target object. For example, a first matrix (or dark measurement matrix) may be calculated, where each row may indicate a magnetic field measurement by one magnetic receiver / sensor of the multiple magnetic receivers 105 and each column may indicate a measurement time.

[0053] The determining may include transforming the received data characterizing the signal from a first basis to a second basis. The received data characterizing the signal may be a vector that may include various measurements associated with the detection of the target object (e.g., detected by the magnetic receiver 105 at various measurements). The transformation may be accomplished by multiplying the received signal data (e.g., having a vector form) by a second matrix. The second matrix may be computable by singular value decomposition of the dark measurement matrix (e.g., see Equation 3 below). For example, the second matrix (e.g., matrix (U) in Equation 3) may be multiplied by a second matrix. (f) ) * is the dark measurement matrix (e.g., the matrix d in Eq. 3) (f) ) may include the left singular vectors of

[0054] Determining may further include modifying the transformed data (e.g., a product of the vector of data received in step 202 and a second matrix) to generate modified data. In some embodiments, generating the modified data may include canceling portions of the transformed data that may be indicative of (or may be affected by) external interference. This can be done, for example, by projecting the transformed data onto one or more predetermined basis vectors indicative of a magnetic field generated by the second object, and canceling (or removing) the projected components from the transformed data.

[0055] In some embodiments, canceling the aforementioned components of the transformed data may be achieved by subtracting the diagonal matrix obtained from the singular value decomposition of the dark measurement matrix (e.g., the diagonal matrix S in Equation 3 below). (f) ) and modifying the modified diagonal matrix (e.g., the modified diagonal matrix D N ) by the vector of transformed data to generate a vector of modified data. In some embodiments, the modified diagonal matrix may be a diagonal matrix (e.g., S (f) ) by replacing one or more singular values ​​equal to or greater than a predetermined value in the diagonal elements of the diagonal matrix (e.g., S (f) ) by replacing one or more singular values ​​in the diagonal elements of (x,y) that are less than or equal to a predetermined value with 1.

[0056] The modified data (e.g., a vector of transformed data) may be transformed from the second basis to the first basis. This can be done, for example, by applying a matrix U (f) (The conjugate of the matrix (U (f) ) * ) The process of transforming the measurement signals from the target object from a first basis to a second basis, modifying the transformed signals, and transforming the modified signals back to the first basis is described below in Equations 9-11.

[0057] In some embodiments, the properties of the target object (e.g., polarizability) can be calculated using a transfer matrix (e.g., H (f) ) to the measurement of the magnetic field from the target object.

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[0058] FIG. 4 illustrates an exemplary interference signal (left) and an exemplary target object signal (right). The interference signal has three components oriented along the x-, y-, and z-axes. The target object signal has an orientation along the y-axis (shown in orange). FIG. 5 illustrates a superimposed signal (left) generated by superimposing the interference signal and the measurement signal of FIG. 4, and a transformed superimposed signal (right). The transformed superimposed signal can be obtained by transforming the superimposed signal from a first basis (x-, y-, z-axes) to a second basis (1-, 2-, and 3-axes). After transformation, the noise from the interference signal is mainly along the 1-axis.

[0059] Figure 6 shows an exemplary modified signal (left side) calculated by canceling a portion of an interfering signal from the transformed superimposed signal of Figure 5. For example, an interfering signal present along the 1-axis is canceled. After canceling the 1-axis signal, the modified signal is transformed back to the first basis (second transformed signal). The second transformed signal is plotted on the right side.

[0060] In some embodiments, time-varying magnetic fields induced in the receiver by small displacements and / or rotations of the receiver (e.g., magnetic receiver 105) may be identified and corrected. This can be done, for example, by performing a Taylor expansion of the measurement signal from the transmitter (e.g., assuming that the distance of the transmitter is much larger than the displacement of the magnetic receiver 105) and considering only linear terms (e.g., see Equation 16 below). The location and orientation of the magnetic receiver may be considered as a function of time. In some embodiments, the degrees of freedom of movement of any subset of the receivers may be assumed to be limited to two (e.g., based on the inclination of the receivers within a common mechanical structure with a base at a fixed location). Based on these considerations, a measurement matrix (e.g., similar to the dark measurement matrix described above) can be calculated and decomposed using singular value decomposition.

[0061] Illustrative examples are described below.

[0062] Inspection systems may encounter external sources of noise or interference in the real world that obscure signals from the real object being tested. These sources may have fairly arbitrary time dependence (e.g., if the source is stationary). For example, currents in nearby power lines may generate magnetic fields that may affect the test receiver. The magnetic field generated by the power lines may be centered at 60 Hz (or 50 Hz in Europe), but variable loads may cause side lobes that fall within the band of interest of the inspection system and thus survive various hardware and digital filters in the post-processing architecture of the inspection system.

[0063] Assuming that both the system and some N interference sources are not moving relative to each other, for a given carrier frequency (ω f ) is a function with arbitrary spatial dependence for each independent interferer.

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[0064] See, for example, Figure 3. Note that the interferer does not have to be physically small or localized, it only needs to be stationary. Dark measurements may be collected (e.g., measurements where all internal transmissions are turned off and only external interference contributes). Time

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[0065] For characterization using singular value decomposition, a set of discrete magnetic field measurements collected by the system while in the “dark” is given by:

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[0066] The assumption that the interferers are orthogonal is not necessary for the operation of the method, but may provide a desirable physical interpretation of the modes recovered by SVD. If the interferers are not in fact orthogonal, the method may be able to find the fewest orthogonal modes that can describe the totality of the external interference; the only part of the method that is disabled is the one-to-one mapping between the singular vectors and the interferers.

[0067] For estimation and subtraction using dot products, previous characterizations may be used to remove the contribution from external interference in future measurements when the transmitter is turned on.

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[0068] The current time dependence of the interferer can be calculated by applying our known spatial modes to the measured data using a dot product, or

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[0069] In this way, the time dependence of the interferer may be recovered. In some embodiments, a term related to the desired measurement may be left behind. If the spatial modes of the desired measurement and the interferer are quite different (e.g., nearly orthogonal), this first term may approach zero and satisfy:

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[0070] The last line, where the interference terms have vanished, may be expressed in matrix form as

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[0071] This formalism may make explicit the operation of expanding the null space of the system's transfer matrix to include the spatial modes of external interferers. In other words, in some embodiments, the transfer matrix is ​​modified such that no amount of signal from an identified interferer will result in a valid measurement vector.

[0072] If the original transfer matrix is ​​assumed to have rank K, then the rank of the effective transfer matrix is

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[0073] Adding a regularizer can provide an improvement with respect to any loss in transfer matrix rank. Indeed, combining regularization with this procedure may make it possible to use rational predecessors to fill in any potential information gaps after filtering out potentially noisy measurements.

[0074] With respect to applications to signals induced by motion, the method described herein may be applied to any unwanted signal that can be characterized by a collection of time-invariant spatial modes. In this section, the method has been applied to the example of a small displacement / rotation of a sensor in the primary magnetic field. With respect to signals induced by coordinated motion of multiple sensors, the physical enclosure may be tilted or swayed when exposed to wind. If the sensors move (and / or rotate) in a non-uniform primary field, their sampling of the primary magnetic field at different points in space over a given time may result in a dynamic signal of a magnitude equal to or greater than the desired secondary magnetic field. This may be problematic for algorithms that consume this data. In some embodiments, if the displacement is assumed to be small relative to the distance to the primary magnetic field source, the signal may be expanded using a Taylor expansion to include linear terms (e.g., the product of the displacement and the derivative of the primary magnetic field with respect to this displacement). Compared to the previous section, the displacement as a function of time may play the role of θ(τ) and the magnetic field gradient is

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[0075] In some embodiments, when the exact nature of the magnetic field gradient or motion is unknown, the mode may be characterized empirically (e.g., as in the case of an external interferer). For example, assuming no other signals are present, the system will (f) The dark measurement d may be subjected to random motion over a period of time to measure d, which may include independent contributions from various modes of motion. (f)Using this motion measurement instead of , the same procedure as outlined in the previous section may be followed. The method may be effective if the nature of the motion characterized encompasses certain motions experienced in live operation. If the system is equipped with a means to automatically perturb its own position, this could form an automated site-specific calibration routine similar to that described below for the case of external interference. In some embodiments, all modes may be orthogonal to simultaneously suppress external interference and motion-induced signals using this method. This can be achieved by characterizing multiple modes serially (e.g., by first characterizing a mode of one nature and then applying the resulting transformation to the data before characterizing a mode of a second nature).

[0076] The above-described exemplary method for characterizing and suppressing external interference may be implemented in the following examples. Before screening begins, the system should collect "dark" measurements, or measurements with the transmit coil turned off. The collected data is then analyzed using SVD at each frequency. The spatial distribution of significant external sources (φ (f,n) ) (e.g., singular vectors with singular values ​​above some threshold) are stored.

[0077] The transfer matrix is ​​modified according to equation (14) and stored along with its pseudoinverse. During live operation, collected data is transformed according to equation (9) before the polarizability search is performed.

[0078] Even though the spatial modes of interferers and real objects passing through the system are very different, they may not be expected (or required) to be orthogonal. This procedure may therefore have a significant effect on the data measured in normal operation. Two aspects of some embodiments include: 1) the modification is linear; and 2) the transfer matrix used during inversion / search is modifiable in the same way as the data is modified. For these reasons, the predicted power of the model may not be reduced by interference suppression. Setting a threshold for external sources may be based on singular values, since these represent the amplitude of the interference (albeit at the time of characterization). Some other metric may be introduced in relation to the reduction of the rank of the potential transfer matrix to avoid including interferer modes that may significantly impair performance. Formally, the safest mode to eliminate may satisfy the following equation:

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[0079] As in the case of interferers far from the system, slow spatial variations may be a reasonable proxy. Some of the proposed embodiments may require that the interferer be present when the dark measurements are collected. Intermittent interferers may present challenges to this method. For more complete coverage, a complementary routine may be required that periodically monitors for new interferers and recommends new dark measurements. Moving the system (or interference source) may destroy the recorded spatial mode associations, and the procedure may then be repeated. A nearby inspection system that is turned on when the dark measurements are collected may be identified as an interferer.

[0080] Although a few variations have been described in detail above, other modifications or additions are possible. For example, the number of receivers may not be limited and some embodiments may include any number of receivers. The transmitters are not limited to a particular frequency and may, for example, use coils with different characteristics (operating frequency, location, etc.). Different reconstruction algorithms may be used, and different features may be used for threat detection.

[0081] Without limiting in any way to the scope, interpretation, or application of the appended claims, technical effects of one or more of the exemplary embodiments disclosed herein may include one or more of the following, for example, some exemplary embodiments of the present subject matter may perform threat detection and discrimination in high clutter environments where individuals may be carrying personal items such as cellular phones and laptops, and without confiscating personal items. In some embodiments, a personnel screening system may perform threat detection and discrimination at a high throughput, thereby allowing individuals to pass through a metal detector at a normal walking speed and without requiring the individual to slow down to be screened, and in some embodiments, a screening boundary may allow multiple individuals to pass through the boundary alongside one another (e.g., two or more people abreast). In some configurations, individuals walking nearby may be screened, thereby eliminating the need for the screened individual to remain stationary during the screening process.

[0082] One or more aspects or features of the subject matter described herein may be implemented in digital electronic circuitry, integrated circuits, specially designed application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) computer hardware, firmware, software, and / or combinations thereof. These various aspects or features may include the implementation of one or more computer programs executable and / or interpretable on a programmable system including at least one programmable processor, which may be special purpose or general purpose, connected to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device. The programmable system or computing system may include clients and servers. The clients and servers are generally located remotely from one another and typically interact with each other through a communications network. The relationship of client and server arises by virtue of computer programs running in the respective computers and having a client-server relationship to each other.

[0083] In view of the above-mentioned subject matter embodiments, the present application discloses the following list of embodiments, in which any one feature of an embodiment individually, or more than one feature of the above embodiment in combination, and optionally in combination with one or more features of one or more other embodiments, are further embodiments within the disclosure of this application.

[0084] Example 1: The method is: receiving data characterizing signals acquired by a plurality of magnetic field receivers formed from a combination of a first magnetic field, a second magnetic field resulting from an interaction of the first magnetic field with a first object, and a third signal resulting from a movement of a receiver within the first magnetic field and / or within an external magnetic field other than the first magnetic field generated by an external source; determining a component of the signal characterizing a contribution of the second magnetic field to the signal, the determining comprising at least multiplying the received data by a mapping characterizing a contribution of the third signal to the signal to cancel the contribution of the third signal; providing said determined component of a signal characterizing a contribution of said second magnetic field to said signal; include.

[0085] Example 2: The method of Example 1, comprising: The above decision is transforming received data characterizing the signal from a first basis to a second basis; modifying the transformed data by at least canceling a portion of the transformed data that corresponds to a projection of the transformed data on predetermined basis vectors indicative of a magnetic field generated by a second object to generate modified data; and converting the modified data from the second basis to the first basis.

[0086] Example 3: Any of the methods of Examples 1 and 2 is calculating a first matrix indicative of magnetic field measurements associated with a magnetic field generated by the external source in the absence of the first magnetic field; performing a singular value decomposition on the first matrix to generate a second matrix including a plurality of left singular vectors of the first matrix and a third matrix including singular values ​​associated with the first matrix on a diagonal of the third matrix; Further includes:

[0087] Example 4: Any of the methods of Examples 1 to 3, Transforming the received data from the first basis to the second basis includes multiplying the received data by the second matrix.

[0088] Example 5: Any of the methods of Examples 1 to 4, generating a fourth matrix by at least setting first singular values ​​in a diagonal element of the third matrix that are greater than or equal to a predetermined value to zero, and setting second singular values ​​in a diagonal element of the third matrix that are less than the predetermined value to one; a first left singular vector of the plurality of left singular vectors is associated with the first singular value; The predetermined basis vectors indicative of the magnetic field generated by the second object include the first left singular vector.

[0089] Example 6: Any of the methods of Examples 1 to 5, Modifying the transformed data includes multiplying a result of the multiplication between the received data and the second matrix by the fourth matrix.

[0090] Example 7: Any of the methods of Examples 1 to 6, Transforming the modified data from the second basis to the first basis includes multiplying the modified data with a transpose of the second matrix.

[0091] Example 8: Any of the methods of Examples 1 to 7, The method further includes calculating a polarizability of the target object characterizing a magnetic polarization property of the target object from the determined component of the signal characterizing a contribution of the second magnetic field to the signal.

[0092] Example 9: Any of the methods of Examples 1 to 8, calculating a fifth matrix indicative of magnetic field measurements resulting from a rotation of one or more of the plurality of magnetic field receivers about a predetermined axis; A matrix element of the fifth matrix associated with a first magnetic field receiver is calculated by multiplying an angular displacement of the first magnetic field receiver by at least a predetermined expansion of a mode of the first magnetic field receiver associated with the angular displacement.

[0093] Example 10: Any of the methods of Examples 1 to 9, The first object is a target object being inspected and the second object is a stationary interfering object.

[0094] Example 11: The system is at least one data processor; a memory coupled to the at least one data processor; The above memory is receiving data characterizing signals acquired by a plurality of magnetic field receivers formed from a combination of a first magnetic field, a second magnetic field resulting from an interaction of the first magnetic field with a first object, and a third signal resulting from a movement of a receiver within the first magnetic field and / or within an external magnetic field other than the first magnetic field generated by an external source; determining a component of the signal characterizing a contribution of the second magnetic field to the signal, the determining comprising at least multiplying the received data by a mapping characterizing a contribution of the third signal to the signal to cancel the contribution of the third signal; and providing the determined component of a signal characterizing a contribution of the second magnetic field to the signal.

[0095] Example 12: 11. The system of claim 11, The above decision is transforming received data characterizing the signal from a first basis to a second basis; modifying the transformed data by at least canceling a portion of the transformed data that corresponds to a projection of the transformed data on predetermined basis vectors indicative of a magnetic field generated by a second object to generate modified data; and converting the modified data from the second basis to the first basis.

[0096] Example 13: A system according to any one of Examples 11 to 12, The above operation is calculating a first matrix indicative of magnetic field measurements associated with a magnetic field generated by the external source in the absence of the first magnetic field; and performing a singular value decomposition on the first matrix to generate a second matrix including a plurality of left singular vectors of the first matrix and a third matrix including singular values ​​associated with the first matrix in its diagonal components.

[0097] Example 14: A system according to any one of Examples 11 to 13, Transforming the received data from the first basis to the second basis includes multiplying the received data by the second matrix.

[0098] Example 15: A system according to any one of Examples 11 to 14, the operations further include generating a fourth matrix by at least setting first singular values ​​in a diagonal element of the third matrix that are greater than or equal to a predetermined value to zero, and setting second singular values ​​in a diagonal element of the third matrix that are less than the predetermined value to one; a first left singular vector of the plurality of left singular vectors is associated with the first singular value; The predetermined basis vectors indicative of the magnetic field generated by the second object include the first left singular vector.

[0099] Example 16: A system according to any one of Examples 11 to 15, Modifying the transformed data includes multiplying a result of the multiplication between the received data and the second matrix by the fourth matrix.

[0100] Example 17: A system according to any one of Examples 11 to 16, Transforming the modified data from the second basis to the first basis includes multiplying the modified data with a transpose of the second matrix.

[0101] Example 18: A system according to any one of Examples 11 to 17, The operations further include calculating a polarizability of the target object characterizing a magnetic polarization property of the target object from the determined component of the signal characterizing a contribution of the second magnetic field to the signal.

[0102] Example 19: The system according to any one of Examples 11 to 18, The operations further include calculating a fifth matrix indicative of magnetic field measurements resulting from a rotation of one or more of the plurality of magnetic field receivers about a predetermined axis; A matrix element of the fifth matrix associated with a first magnetic field receiver is calculated by multiplying an angular displacement of the first magnetic field receiver by at least a predetermined expansion of a mode of the first magnetic field receiver associated with the angular displacement.

[0103] Example 20: A system according to any one of Examples 11 to 19, The first object is a target object being inspected and the second object is a stationary interfering object.

[0104] Example 21: 1. A computer program product comprising: a non-transitory machine-readable medium storing instructions that, when executed by at least one programmable processor having at least one physical core and a plurality of logical cores, cause the at least one programmable processor to perform the following operations: The above operation is receiving data characterizing signals acquired by a plurality of magnetic field receivers formed from a combination of a first magnetic field, a second magnetic field resulting from an interaction of the first magnetic field with a first object, and a third signal resulting from a movement of a receiver within the first magnetic field and / or within an external magnetic field other than the first magnetic field generated by an external source; determining a component of the signal characterizing a contribution of the second magnetic field to the signal, the determining comprising at least multiplying the received data by a mapping characterizing a contribution of the third signal to the signal to cancel the contribution of the third signal; and providing the determined component of the signal characterizing a contribution of the second magnetic field to the signal.

[0105] Example 22: 22. The computer program product of Example 21, The above decision is transforming received data characterizing the signal from a first basis to a second basis; modifying the transformed data by at least canceling a portion of the transformed data that corresponds to a projection of the transformed data on predetermined basis vectors indicative of a magnetic field generated by a second object to generate modified data; and converting the modified data from the second basis to the first basis.

[0106] Example 23: 23. The computer program product of any one of Examples 21-22, The above operation is calculating a first matrix indicative of magnetic field measurements associated with a magnetic field generated by the external source in the absence of the first magnetic field; and performing a singular value decomposition on the first matrix to generate a second matrix including a plurality of left singular vectors of the first matrix and a third matrix including singular values ​​associated with the first matrix in its diagonal components.

[0107] Example 24: A computer program product according to any one of Examples 21 to 23, Transforming the received data from the first basis to the second basis includes multiplying the received data by the second matrix.

[0108] Example 25: A computer program product according to any one of Examples 21 to 24, the operations further include generating a fourth matrix by at least setting first singular values ​​in a diagonal element of the third matrix that are greater than or equal to a predetermined value to zero, and setting second singular values ​​in a diagonal element of the third matrix that are less than the predetermined value to one; a first left singular vector of the plurality of left singular vectors is associated with the first singular value; The predetermined basis vectors indicative of the magnetic field generated by the second object include the first left singular vector.

[0109] Example 26: A computer program product according to any one of Examples 21 to 25, Modifying the transformed data includes multiplying a result of the multiplication between the received data and the second matrix by the fourth matrix.

[0110] Example 27: A computer program product according to any one of Examples 21 to 26, Transforming the modified data from the second basis to the first basis includes multiplying the modified data with a transpose of the second matrix.

[0111] Example 28: A computer program product according to any one of Examples 21 to 27, The operations further include calculating a polarizability of the target object characterizing a magnetic polarization property of the target object from the determined component of the signal characterizing a contribution of the second magnetic field to the signal.

[0112] Example 29: The computer program product of any of Examples 21 to 28, The operations further include calculating a fifth matrix indicative of magnetic field measurements resulting from a rotation of one or more of the plurality of magnetic field receivers about a predetermined axis; A matrix element of the fifth matrix associated with a first magnetic field receiver is calculated by multiplying an angular displacement of the first magnetic field receiver by at least a predetermined expansion of a mode of the first magnetic field receiver associated with the angular displacement.

[0113] Example 30: A computer program product according to any one of Examples 21 to 29, The first object is a target object being inspected and the second object is a stationary interfering object.

[0114] Example 31: The system is means for receiving data characterizing signals acquired by a plurality of magnetic field receivers formed from a combination of a first magnetic field, a second magnetic field resulting from an interaction of said first magnetic field with a first object, and a third signal resulting from a movement of the receivers within said first magnetic field and / or within an external magnetic field other than said first magnetic field generated by an external source; means for determining a component of the signal characterizing a contribution of the second magnetic field to the signal, the determining comprising at least multiplying the received data by a mapping characterizing a contribution of the third signal to the signal to cancel the contribution of the third signal; and means for providing said determined component of a signal characterizing a contribution of said second magnetic field to said signal.

[0115] Example 32: The system of Example 31 is The present invention further includes a means for executing any of the functions recited in any of claims 2 to 10.

[0116] These computer programs may be referred to as programs, software, software applications, applications, components, or codes, and these computer programs include machine instructions for a programmable processor and may be implemented in high-level procedural languages, object-oriented programming languages, functional programming languages, logic programming languages, and / or assembly / machine languages. As used herein, the term "machine-readable medium" refers to any computer program product, apparatus, and / or device used to provide machine instructions and / or data to a programmable processor, such as, for example, magnetic disks, optical disks, memories, programmable logic circuits (PLDs), and includes machine-readable media that receive machine instructions as machine-readable signals. The term "machine-readable signal" refers to any signal used to provide machine instructions and / or data to a programmable processor. Machine-readable media may non-transiently store such machine instructions, such as, for example, a non-transient solid-state memory or a magnetic hard drive or any equivalent storage medium. Machine-readable media may alternatively or additionally store such machine instructions temporarily, such as, for example, a processor cache or other random access memory associated with one or more physical processor cores.

[0117] To interact with a user, one or more aspects or features of the subject matter described herein can be implemented on a computer having a display device, such as a cathode ray tube (CRT) or liquid crystal display (LCD) or light emitting diode (LED) monitor, for displaying information to the user, and a keyboard and a pointing device, such as a mouse or trackball, that the user may use to provide input to the computer. Other types of devices can be used to interact with the user as well. For example, feedback provided to the user may be any form of sensory feedback, such as visual feedback, auditory feedback, or tactile feedback. Input from the user may be received in any form, including, but not limited to, voice, speech, or tactile input. Other possible input devices include, but are not limited to, touch screens or other touch-sensitive devices, such as single or multi-point resistive or capacitive trackpads, voice recognition hardware and software, optical scanners, optical pointers, digital image capture devices and associated interpretation software, and the like.

[0118] In the above detailed description and claims, phrases such as "at least one" or "one or more" may appear after a conjunctive list of elements or features. The term "and / or" may appear in a list of two or more elements or features. These phrases are intended to mean any of the listed elements or features individually, or any of the described elements or features in combination with any of the other described elements or features, unless otherwise implicitly or explicitly stated in the context of their use. For example, the phrases "at least one of A and B," "one or more of A and B," and "A and / or B" mean "A only, B only, or both A and B," respectively. A similar interpretation is intended for lists containing more than two items. For example, the phrases "at least one of A, B, and C," "one or more of A, B, and C," and "A, B, and / or C" are intended to mean "A only, B only, C only, both A and B, both A and C, both B and C, or all of A, B, and C," respectively. Furthermore, use of the term "based on" above and in the claims is intended to mean "based at least in part on," such that there may be unrecited features or components.

[0119] The subject matter described herein may be embodied as a system, an apparatus, a method, and / or an article, depending on the desired configuration. The embodiments set forth in the above description do not represent all embodiments applicable to the subject matter described herein. Instead, they are merely some examples applicable to aspects related to the described address. Although a few variations have been described in detail above, other modifications or additions are possible. In particular, other features and / or variations may be provided in addition to those described herein. For example, the embodiments described above may relate to various combinations and subcombinations of the disclosed features, and may relate to combinations and subcombinations of several other features disclosed above. Furthermore, the logic flows illustrated in the accompanying drawings and / or described herein do not necessarily require the particular order shown or sequential order to achieve desirable results. Other embodiments may be within the scope of the appended claims.

Claims

1. receiving data characterizing signals acquired by a plurality of magnetic field receivers formed from a combination of a first magnetic field, a second magnetic field resulting from an interaction of the first magnetic field with a first object, and a third signal resulting from movement of the receivers within the first magnetic field and / or within an external magnetic field other than the first magnetic field generated by an external source; determining a component of the signal characterizing the contribution of the second magnetic field to the signal, the determining the component comprising at least multiplying the received data by a mapping characterizing the contribution of the third signal to the signal to cancel the contribution of the third signal; providing the determined component of the signal characterizing a contribution of the second magnetic field to the signal. method.

2. The above decision is transforming received data characterizing the signal from a first basis to a second basis; modifying the transformed data by at least canceling a portion of the transformed data corresponding to a projection of the transformed data onto predetermined basis vectors indicative of a magnetic field generated by a second object to produce modified data; and converting the modified data from the second basis to the first basis. The method of claim 1.

3. calculating a first matrix indicative of magnetic field measurements associated with a magnetic field generated by the external source in the absence of the first magnetic field; performing singular value decomposition on the first matrix to generate a second matrix including a plurality of left singular vectors of the first matrix and a third matrix including singular values ​​associated with the first matrix on its diagonal elements. The method of claim 2.

4. converting the received data from the first basis to the second basis includes multiplying the received data by the second matrix; The method of claim 3.

5. The method further includes generating a fourth matrix by at least setting first singular values ​​in a diagonal element of the third matrix that are greater than or equal to a predetermined value to zero, and setting second singular values ​​in a diagonal element of the third matrix that are less than the predetermined value to one; a first left singular vector of the plurality of left singular vectors is associated with the first singular value; the predetermined basis vectors indicative of the magnetic field generated by the second object include the first left singular vector; The method of claim 4.

6. modifying the transformed data includes multiplying a result of the multiplication between the received data and the second matrix by the fourth matrix; The method of claim 5.

7. converting the modified data from the second basis to the first basis includes multiplying the modified data by the transpose of the second matrix. The method of claim 6.

8. calculating a polarizability of the target object characterizing a magnetic polarization property of the target object from the determined component of the signal characterizing the contribution of the second magnetic field to the signal. The method of claim 1.

9. The method further includes calculating a fifth matrix indicative of magnetic field measurements resulting from rotation of one or more of the plurality of magnetic field receivers about a predetermined axis; a matrix element of the fifth matrix associated with a first magnetic field receiver is calculated by multiplying an angular displacement of the first magnetic field receiver by at least a predetermined expansion of a mode of the first magnetic field receiver associated with the angular displacement; The method of claim 2.

10. the first object is a target object being inspected and the second object is a stationary interfering object; The method of claim 1.

11. at least one data processor; a memory connected to the at least one data processor, The above memory is receiving data characterizing signals acquired by a plurality of magnetic field receivers formed from a combination of a first magnetic field, a second magnetic field resulting from an interaction of the first magnetic field with a first object, and a third signal resulting from movement of the receivers within the first magnetic field and / or within an external magnetic field other than the first magnetic field generated by an external source; determining a component of the signal characterizing the contribution of the second magnetic field to the signal, the determining the component comprising at least multiplying the received data by a mapping characterizing the contribution of the third signal to the signal to cancel the contribution of the third signal; and providing the determined component of the signal characterizing the contribution of the second magnetic field to the signal. system.

12. The above decision is transforming received data characterizing the signal from a first basis to a second basis; modifying the transformed data by at least canceling a portion of the transformed data corresponding to a projection of the transformed data onto predetermined basis vectors indicative of a magnetic field generated by a second object to produce modified data; and converting the modified data from the second basis to the first basis. The system of claim 11.

13. The above operation is calculating a first matrix indicative of magnetic field measurements associated with a magnetic field generated by the external source in the absence of the first magnetic field; performing singular value decomposition on the first matrix to generate a second matrix including a plurality of left singular vectors of the first matrix and a third matrix including singular values ​​associated with the first matrix on its diagonal elements. The system of claim 12.

14. converting the received data from the first basis to the second basis includes multiplying the received data by the second matrix; The system of claim 13.

15. the operations further include generating a fourth matrix by at least setting first singular values ​​in the diagonal elements of the third matrix that are greater than or equal to a predetermined value to zero, and setting second singular values ​​in the diagonal elements of the third matrix that are less than the predetermined value to one; a first left singular vector of the plurality of left singular vectors is associated with the first singular value; the predetermined basis vectors indicative of the magnetic field generated by the second object include the first left singular vector; 15. The system of claim 14.

16. modifying the transformed data includes multiplying a result of the multiplication between the received data and the second matrix by the fourth matrix; 16. The system of claim 15.

17. converting the modified data from the second basis to the first basis includes multiplying the modified data by the transpose of the second matrix.

17. The system of claim 16.

18. the operations further include calculating a polarizability of the target object characterizing a magnetic polarization property of the target object from the determined component of the signal characterizing the contribution of the second magnetic field to the signal. The system of claim 11.

19. The operations further include calculating a fifth matrix indicative of magnetic field measurements resulting from rotation of one or more of the plurality of magnetic field receivers about a predetermined axis; a matrix element of the fifth matrix associated with a first magnetic field receiver is calculated by multiplying an angular displacement of the first magnetic field receiver by at least a predetermined expansion of a mode of the first magnetic field receiver associated with the angular displacement; The system of claim 12.

20. the first object is a target object being inspected and the second object is a stationary interfering object; The system of claim 11.

21. 1. A computer program product comprising: a non-transitory machine-readable medium storing instructions that, when executed by at least one programmable processor having at least one physical core and a plurality of logical cores, cause the at least one programmable processor to perform the following operations: The above operation is receiving data characterizing signals acquired by a plurality of magnetic field receivers formed from a combination of a first magnetic field, a second magnetic field resulting from an interaction of the first magnetic field with a first object, and a third signal resulting from movement of the receivers within the first magnetic field and / or within an external magnetic field other than the first magnetic field generated by an external source; determining a component of the signal characterizing the contribution of the second magnetic field to the signal, the determining the component comprising at least multiplying the received data by a mapping characterizing the contribution of the third signal to the signal to cancel the contribution of the third signal; providing the determined component of the signal characterizing a contribution of the second magnetic field to the signal. Computer program products.

22. The above decision is transforming received data characterizing the signal from a first basis to a second basis; modifying the transformed data by at least canceling a portion of the transformed data corresponding to a projection of the transformed data onto predetermined basis vectors indicative of a magnetic field generated by a second object to produce modified data; and converting the modified data from the second basis to the first basis.

22. The computer program product of claim 21.

23. The above operation is calculating a first matrix indicative of magnetic field measurements associated with a magnetic field generated by the external source in the absence of the first magnetic field; performing singular value decomposition on the first matrix to generate a second matrix including a plurality of left singular vectors of the first matrix and a third matrix including singular values ​​associated with the first matrix on its diagonal elements.

23. The computer program product of claim 22.

24. converting the received data from the first basis to the second basis includes multiplying the received data by the second matrix; 24. The computer program product of claim 23.

25. The operations further include generating a fourth matrix by at least setting first singular values ​​in the diagonal elements of the third matrix that are greater than or equal to a predetermined value to zero, and setting second singular values ​​in the diagonal elements of the third matrix that are less than the predetermined value to one. a first left singular vector of the plurality of left singular vectors is associated with the first singular value; the predetermined basis vectors indicative of the magnetic field generated by the second object include the first left singular vector; 25. The computer program product of claim 24.

26. modifying the transformed data includes multiplying a result of the multiplication between the received data and the second matrix by the fourth matrix; 26. The computer program product of claim 25.

27. converting the modified data from the second basis to the first basis includes multiplying the modified data by the transpose of the second matrix.

27. The computer program product of claim 26.

28. the operations further include calculating a polarizability of the target object characterizing a magnetic polarization property of the target object from the determined component of the signal characterizing the contribution of the second magnetic field to the signal.

22. The computer program product of claim 21.

29. The operations further include calculating a fifth matrix indicative of magnetic field measurements resulting from rotation of one or more of the plurality of magnetic field receivers about a predetermined axis; a matrix element of the fifth matrix associated with a first magnetic field receiver is calculated by multiplying an angular displacement of the first magnetic field receiver by at least a predetermined expansion of a mode of the first magnetic field receiver associated with the angular displacement; 23. The computer program product of claim 22.

30. the first object is a target object being inspected and the second object is a stationary interfering object; 22. The computer program product of claim 21.

31. means for receiving data characterizing signals acquired by a plurality of magnetic field receivers formed from a combination of a first magnetic field, a second magnetic field resulting from an interaction of said first magnetic field with a first object, and a third signal resulting from movement of the receivers within said first magnetic field and / or within an external magnetic field other than said first magnetic field generated by an external source; means for determining a component of the signal characterizing the contribution of the second magnetic field to the signal, the component determining comprising at least multiplying the received data by a mapping characterizing the contribution of the third signal to the signal to cancel the contribution of the third signal; and means for providing the determined component of the signal characterizing the contribution of the second magnetic field to the signal. system.

32. Further comprising means for performing any of the functions of any of claims 2 to 10, 32. The system of claim 31.

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