A magnetic target positioning method, device, medium and system

Abstract

This application provides a method, apparatus, medium, and system for magnetic target localization. The method includes: acquiring observed values ​​of the measurement area where the magnetic target to be located is located; establishing a target physical model based on a magnetic dipole model; inputting a set of hypothetical magnetic target position parameters and magnetic moment parameters into the target physical model to obtain theoretical predicted values, wherein the theoretical predicted values ​​include theoretical values ​​of the magnetic gradient tensor and the total magnetic field strength; constructing an objective function based on the difference between the theoretical predicted values ​​and the corresponding observed values; and adjusting the hypothetical magnetic target position parameters and magnetic moment parameters through an optimization algorithm to minimize the objective function and obtain the position coordinates of the magnetic target. Some embodiments of this application can accurately determine the position information of a magnetic target using only single-point (or finite-point) observation data, overcoming the technical bottleneck of existing single-point magnetic gradient tensor localization methods.

Description

Technical Field

[0001] This application relates to the field of magnetic source positioning, and more specifically, the embodiments of this application relate to a magnetic target positioning method, apparatus, medium, and system. Background Technology

[0002] Magnetic target detection and positioning technology has important application value in military, security, resource exploration and engineering inspection fields. For example, it can be used for unexploded ordnance detection, underground pipeline location or geological structure investigation.

[0003] The magnetic gradient tensor of a single-point measurement can only provide the unit vectors of the magnetic moment vector and the position vector from the magnetic target to the measurement point. Without prior conditions, it is difficult to achieve single-point localization of the magnetic target by only obtaining the magnetic gradient tensor information.

[0004] Therefore, how to better locate magnetic targets by compensating for the inadequacy of single-point magnetic gradient tensor information without significantly increasing system hardware complexity and cost is a technical challenge that urgently needs to be solved in this field. Summary of the Invention

[0005] The purpose of this application is to provide a magnetic target positioning method, device, medium and system. Some embodiments of this application construct a total field theoretical calculation model with the geomagnetic field background observation value as a necessary input, and combine it with the magnetic gradient tensor theoretical model to calculate the theoretical value of magnetic field properties. Thus, the position information of the magnetic target can be accurately determined using only single-point (or limited-point) observation data, which solves the technical bottleneck that the existing single-point magnetic gradient tensor cannot locate the target.

[0006] In a first aspect, embodiments of this application provide a magnetic target localization method, the method comprising: acquiring observed values ​​of magnetic field properties of the region where the magnetic target to be located is located, wherein the observed values ​​include: observed values ​​of magnetic gradient tensor, observed values ​​of total magnetic field strength, and observed values ​​of geomagnetic field background; establishing a target physical model based on a magnetic dipole model, wherein the target physical model includes a total field theory calculation model and a magnetic gradient tensor theory model, the total field theory calculation model taking the observed values ​​of geomagnetic field background as input; inputting a set of hypothetical magnetic target position parameters and magnetic moment parameters into the target physical model to obtain theoretical prediction values, wherein the theoretical prediction values ​​include theoretical values ​​of magnetic gradient tensor and theoretical values ​​of total magnetic field strength; constructing an objective function based on the difference between the theoretical prediction values ​​and the corresponding observed values; and adjusting the hypothetical magnetic target position parameters and magnetic moment parameters through an optimization algorithm to minimize the objective function and obtain the position coordinates of the magnetic target.

[0007] The embodiments of this application achieve stable and accurate inversion calculations of the position and magnetic moment of magnetic targets by fusing total field and magnetic gradient tensor information and constructing a total field physical model with geomagnetic field background observations as necessary input. This approach effectively overcomes the shortcomings of traditional single-point magnetic gradient tensor positioning methods due to insufficient information, while avoiding fundamental errors caused by simply processing total field data. It improves the feasibility and accuracy of single-point positioning and is particularly suitable for applications such as rapid detection or portable devices.

[0008] In some embodiments, the total magnetic field strength observation is used to characterize the total magnetic field strength of the Earth's magnetic field and the magnetic field generated by the magnetic target at the measurement point location, the magnetic gradient tensor observation is used to characterize the rate of change of the magnetic field vector in space at the measurement point location, and the geomagnetic field background observation is used to characterize the magnetic field vector generated by the Earth's magnetic field when the magnetic target is not present at the measurement point location.

[0009] In some embodiments, the magnetic gradient tensor theoretical model is a magnetic gradient tensor component model, which is used to calculate the theoretical values ​​of multiple independent components of the magnetic gradient tensor, and the total field theoretical calculation model is used to calculate the theoretical value of the total magnetic field strength; the step of constructing an objective function based on the difference between the theoretical prediction value and the corresponding observed value includes: constructing the objective function based on a first difference between the multiple independent components of the observed magnetic gradient tensor and the theoretical values ​​of the corresponding independent components, and a second difference between the observed value of the total magnetic field strength and the corresponding theoretical value.

[0010] Some embodiments of this application employ a magnetic gradient tensor component model, which fully utilizes the complete information of each independent component of the tensor and jointly constructs an objective function with the total field information for inversion. This achieves the most complete constraint and synchronous solution of the six parameters of the magnetic target position and magnetic moment, thereby improving the accuracy of the calculation results.

[0011] In some embodiments, the objective function is the weighted sum of squares or norm of the first difference and the second difference.

[0012] The objective function design of some embodiments of this application integrates the observation errors of the magnetic gradient tensor and the total magnetic field strength in mathematical forms such as weighted sum of squares or norms, achieving unified quantification and synergistic minimization of errors from different sources and with different physical meanings. This design not only provides a differentiable optimization objective for the inversion algorithm, ensuring the numerical stability and convergence of the iterative solution process, but also, by introducing weighting coefficients, endows the method with the ability to flexibly balance the relative importance of the two types of information. This allows for adaptive adjustment based on actual sensor accuracy and scenario requirements, effectively improving the robustness and accuracy of the positioning results.

[0013] In some embodiments, the magnetic gradient tensor theoretical model is a magnetic gradient tensor invariant model; before inputting a set of hypothetical magnetic target position parameters and magnetic moment parameters into the target physical model, the method further includes: performing eigenvalue decomposition on the magnetic gradient tensor observations to determine the unit vector of the position direction from the measurement point to the magnetic target and the unit vector of the magnetic moment direction of the magnetic target; wherein, the hypothetical magnetic target position parameters include the distance between the magnetic target and the measurement point, and the hypothetical magnetic target magnetic moment parameters include the magnetic moment modulus of the magnetic target; the theoretical prediction values ​​include: theoretical invariant values ​​calculated by the magnetic gradient tensor invariant model based on the distance and the magnetic moment modulus, and theoretical total field values ​​calculated by the total field theory calculation model based on geomagnetic field background observations; the construction of an objective function based on the difference between the theoretical prediction values ​​and the corresponding observation values ​​includes: constructing the objective function based on the difference between the invariant observation values ​​calculated from the magnetic gradient tensor observations and the theoretical invariant values, and the difference between the total magnetic field strength observations and the theoretical total field values.

[0014] The embodiments of this application employ a magnetic gradient tensor invariant model and pre-analyze the target's orientation information from observation data, reducing the dimensionality of the unknown parameters to be inverted from six (position coordinates and magnetic moment vector) to two (range and magnetic moment modulus). This improvement allows for positioning to be completed by solving only two equations: the total field and the invariants. This significantly reduces system hardware costs, computational complexity, and power consumption while maintaining single-point positioning capabilities, enhancing the engineering practicality and deployment flexibility of this technology in portable, low-cost detection devices.

[0015] In some embodiments, the step of performing feature decomposition on the magnetic gradient tensor observations to determine the unit vector of the position direction from the measurement point to the magnetic target and the unit vector of the magnetic moment direction of the magnetic target includes: performing feature decomposition on the magnetic gradient tensor observations to obtain multiple sets of candidate combinations of unit vectors of direction and unit vectors of magnetic moment direction; and selecting one set from the multiple sets of combinations of unit vectors of direction and unit vectors of magnetic moment direction as the unit vector of position direction and the unit vector of magnetic moment direction based on preset physical constraints.

[0016] The embodiments of this application introduce a selection mechanism based on physical constraints to select a unique directional solution that conforms to the real physical scenario from multiple sets of mathematical solutions generated by eigenvalue decomposition. This solves the inherent ambiguity problem of virtual solutions in the direct inversion of magnetic gradient tensors, elevating the reliability of direction determination from mathematical probability to physical determinism, thereby ensuring the convergence of subsequent positioning solutions and the unique correctness of the results.

[0017] In some embodiments, the observed total magnetic field strength and the observed magnetic gradient tensor are obtained at a first measurement point and a second measurement point, respectively, and the first measurement point and the second measurement point are spatially different; when establishing the target physical model, the total field theoretical calculation model is constructed based on the positional relationship of the first measurement point relative to the magnetic target, and the magnetic gradient tensor theoretical model is constructed based on the positional relationship of the second measurement point relative to the magnetic target.

[0018] Some embodiments of this application eliminate model errors caused by assuming sensor data from different locations are measured at the same point by distinguishing the acquisition locations of the total field and magnetic gradient tensors in the actual model and constructing the two theoretical models based on their actual measurement point locations. This improves the consistency between the mathematical model and the actual physical system and enhances the adaptability of this technical solution to various actual detection platforms and sensor configurations. Secondly, some embodiments of this application provide a magnetic target positioning device, the magnetic target positioning device comprising: an observation value acquisition module configured to acquire observation values ​​of magnetic field properties of the area where the magnetic target to be located is located, wherein the observation values ​​include: magnetic gradient tensor observation values, total magnetic field strength observation values, and geomagnetic field background observation values; a target physical model construction module configured to establish a target physical model based on a magnetic dipole model, wherein the target physical model includes a total field theoretical calculation model and a magnetic gradient tensor theoretical model, the total field theoretical calculation model taking the geomagnetic field background information as an input; a theoretical prediction value acquisition module configured to input a set of hypothetical magnetic target position parameters and magnetic moment parameters into the target physical model to obtain theoretical prediction values, wherein the theoretical prediction values ​​include theoretical values ​​of the magnetic gradient tensor and theoretical values ​​of the total magnetic field strength; an objective function construction module configured to construct an objective function based on the difference between the theoretical prediction values ​​and the corresponding observation values; and a magnetic target position output module configured to adjust the hypothetical magnetic target position parameters and magnetic moment parameters through an optimization algorithm to minimize the objective function and obtain the position coordinates of the magnetic target.

[0019] Thirdly, some embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed, can implement the magnetic target positioning method as described in any of the embodiments included in the first aspect.

[0020] Fourthly, some embodiments of this application provide a magnetic target positioning system, comprising: a data acquisition unit configured to acquire and transmit observations of magnetic field properties of the area where the magnetic target to be located is located, wherein the observations include: magnetic gradient tensor observations, total magnetic field strength observations, and geomagnetic field background observations; and a host computer for receiving the observations, including a processor and a memory, wherein the memory stores a computer program, and the program, when executed by the processor, can implement the magnetic target positioning method as described in any of the embodiments included in the first aspect. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is an architecture diagram of the magnetic target positioning system provided in an embodiment of this application.

[0023] Figure 2 This is a flowchart of a magnetic target positioning method according to an embodiment of this application.

[0024] Figure 3 This application provides a block diagram of the magnetic target positioning device.

[0025] Figure 4 This is a schematic diagram of the electronic device provided in the embodiments of this application. Detailed Implementation

[0026] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0027] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0028] The inventors of this application discovered in their research that it is difficult to achieve single-point localization of magnetic targets based solely on magnetic gradient tensor information; other information needs to be fused. Among the many available magnetic field signals, total magnetic field strength is a common and easily obtained physical quantity. Single-point localization of magnetic targets can be achieved by fusing total magnetic field strength and magnetic gradient tensor information. However, the total magnetic field strength obtained by optical pumping includes information from both the magnetic target and the Earth's magnetic field, and the measurement result is a vector sum rather than an algebraic sum. Therefore, the total magnetic field strength information of the magnetic target cannot be obtained simply by subtracting the total magnetic field strength measured with and without magnetic anomalies. In order to achieve single-point localization of magnetic targets by fusing total magnetic field strength, the embodiments of this application need to remove the Earth's magnetic field from the total magnetic field strength information measured by optical pumping. Considering that the Earth's magnetic field in local survey areas is relatively stable, after obtaining the Earth's magnetic field (i.e., the geomagnetic field background observation value) through ground base stations, the International Geomagnetic Reference Field (IGRF) model, and the total magnetic field strength information of areas without magnetic anomalies, the three-component model of the magnetic dipole can be used to iteratively obtain the three-dimensional spatial coordinates of the magnetic target.

[0029] At least to address the technical problems raised in the background section, some embodiments of this application provide a magnetic target localization method. This method includes: acquiring observed magnetic field properties at one or more points in the region where the magnetic target to be located is located; establishing a target physical model based on a magnetic dipole model and obtaining theoretical values ​​of the magnetic gradient tensor and the total magnetic field strength, respectively, based on the target physical model. The target physical model includes a total field theoretical calculation model and a magnetic gradient tensor theoretical model (which includes a magnetic gradient tensor component model or a magnetic gradient tensor invariant model), with the target position and magnetic moment as independent variables; comparing the observed values ​​with the theoretical values ​​and constructing an objective function (e.g., least squares error) to measure the difference between the two; and adjusting the target position and magnetic moment through an optimization algorithm to minimize the objective function. The target position at this point is the spatial location of the magnetic target to be located.

[0030] Please refer to Figure 1 , Figure 1 The magnetic target positioning system provided in some embodiments of this application includes a data acquisition layer 110 and a magnetic target positioning engine 120. The data acquisition layer 110 includes a magnetic gradiometer 111, an optically pumped magnetometer 112, and a geomagnetic field reference source 113. The magnetic target positioning engine 120 includes a target physical model library 121 and an iterative optimization module 122.

[0031] A magnetic gradient meter is used to collect the magnetic gradient tensor observations at a measurement location point in the region where a magnetic target to be located is located.

[0032] The optically pumped magnetometer is used to collect the total magnetic field strength observation value at a measurement location point in the area where the magnetic target to be located is located.

[0033] In other words, the data acquisition unit of this application embodiment includes at least one total field magnetometer (such as an optical magnetometer, used to measure the observed total magnetic field strength at the measurement point) and a set of magnetic gradient tensor measuring instruments (such as a magnetic gradiometer composed of multiple fluxgate sensors, used to measure multiple independent components of the magnetic gradient tensor G). The observed total magnetic field strength is a scalar value obtained by the optically pumped magnetometer at the actual measurement point i, representing the total magnetic field strength (i.e., the magnitude of the total magnetic field vector) resulting from the vector synthesis of the Earth's magnetic field and the magnetic field generated by the magnetic target at that measurement point. The observed magnetic gradient tensor is a tensor value (usually represented in matrix form, but with five independent components) obtained by the magnetic gradiometer at the actual measurement point i, representing the rate of change (gradient) of the magnetic field vector in space at that measurement point. Specifically, it is a tensor composed of the derivatives of the three components of the magnetic field vector with respect to the three spatial directions. Due to the passive and irrotational nature of the magnetic field, this tensor is symmetrical and therefore has only five independent components.

[0034] The geomagnetic field reference source 113 is used to acquire geomagnetic field background information in the measurement area. The geomagnetic field reference source, also known as the geomagnetic field reference acquisition unit, can be a communication module connected to the International Geomagnetic Reference Field (IGRF) database or a locally set reference measurement station in a non-magnetic anomaly area. It provides the three-component geomagnetic field vector Be (i.e., the geomagnetic field background observation value) of the area where the magnetic target located in the detection zone is situated. The three-component geomagnetic field vector is a vector value obtained through external references (such as the IGRF model, ground base station, or measurements in a non-magnetic anomaly area), representing the background magnetic field vector generated by the Earth's magnetic field at measurement point i, assuming the absence of a magnetic target.

[0035] The magnetic target localization engine is used to determine the spatial coordinates of the magnetic target to be located based on the observations obtained from the data acquisition layer. The target physical model library is used to store the target physical model established based on the magnetic dipole model. The target physical model includes a total field theory calculation model and a magnetic gradient tensor theory model. The total field theory calculation model takes the position parameters and magnetic moment parameters of the magnetic target and the background information of the geomagnetic field as inputs. The magnetic gradient tensor theory model includes a magnetic gradient tensor component model or a magnetic gradient tensor invariant model.

[0036] The iterative optimization module 122 determines the specific location of the magnetic target to be located based on the observed values ​​and the target physical model read from the target physical model library. The specific working process of this iterative optimization module 122 can be referred to the following description. To avoid repetition, it will not be elaborated on here.

[0037] The following is combined with Figure 2 This application provides an exemplary embodiment of a magnetic target localization method, which includes:

[0038] S110, Obtain the observed values ​​of the magnetic field properties of the area where the magnetic target to be located is located, wherein the observed values ​​include: magnetic gradient tensor observed values, total magnetic field strength observed values, and geomagnetic field background observed values.

[0039] It should be noted that, in some embodiments of this application, the total magnetic field strength observation value is used to characterize the total magnetic field strength of the vector synthesis of the Earth's magnetic field and the magnetic field generated by the magnetic target at the measurement point location, the magnetic gradient tensor observation value is used to characterize the rate of change of the magnetic field vector at the measurement point location in space, and the geomagnetic field background observation value is used to characterize the background magnetic field vector generated by the Earth's magnetic field when there is no magnetic target at the measurement point location.

[0040] For example, in some embodiments of this application, a total field magnetometer (e.g., Figure 1 The total magnetic field strength was measured using an optically pumped magnetometer, and the magnetic gradient tensor was measured using a magnetic gradiometer (such as a gradiometer composed of multiple fluxgate sensors, used to measure multiple independent components of the magnetic gradient tensor G). Geomagnetic background observations were collected using a geomagnetic field reference source.

[0041] S120, establish the target physical model based on the magnetic dipole model.

[0042] It should be noted that the target physical model includes a total field theory calculation model and a magnetic gradient tensor theory model. The total field theory calculation model takes geomagnetic field background information as an input, and the magnetic gradient tensor theory model includes a magnetic gradient tensor component model (as shown in formula (4) below) or a magnetic gradient tensor invariant model (as shown in formula (13) below).

[0043] S130, a set of hypothetical magnetic target position parameters and magnetic moment parameters are input into the target physical model to obtain theoretical prediction values, wherein the theoretical prediction values ​​include theoretical values ​​of magnetic gradient tensor and theoretical values ​​of total magnetic field strength.

[0044] It should be noted that the independent variables of the target physical model in some embodiments of this application include: the position parameters (x0, y0, z0) of the magnetic target, and the magnetic moment vector (m) of the magnetic target. x , m y , m z The known geomagnetic background observation values, i.e., the geomagnetic field vector Be, are also included. The dependent variables of the target physical model, i.e., the outputs, include: the theoretical values ​​of the total magnetic field strength at the measurement points, calculated from the model output by the total field theory. The theoretical value of the magnetic gradient tensor at the measurement point, output by the magnetic gradient tensor theoretical model. The embodiments of this application input the assumed magnetic target position parameters and magnetic moment parameters into the constructed target physical model to obtain theoretical prediction values ​​(including the theoretical value of the total magnetic field strength). Theoretical values ​​of magnetic gradient tensor ).

[0045] S140, Construct an objective function based on the difference between the theoretical prediction and the corresponding observed value.

[0046] For example, in some embodiments of this application, the difference between the theoretical value of the magnetic gradient tensor and the observed value of the magnetic gradient tensor are compared, and the difference between the theoretical value of the total magnetic field strength and the observed value of the total magnetic field strength are compared, and an objective function is constructed based on the two differences obtained.

[0047] S150, by adjusting the assumed magnetic target position parameters and magnetic moment parameters through an optimization algorithm, the position coordinates of the magnetic target are obtained by minimizing the objective function.

[0048] It should be noted that the magnetic target position corresponding to the minimization of the objective function is the positioning result of the magnetic target to be located.

[0049] The implementation principle of S130-S150 above can be summarized as follows:

[0050] Step 1 (forward prediction): Given a set of guessed magnetic target locations and magnetic moments (independent variables), and combined with the known geomagnetic field vector (i.e., geomagnetic field background observation values), the corresponding theoretical prediction values ​​(i.e., theoretical values ​​of magnetic gradient tensor and total magnetic field strength) are calculated forward using the target physical model.

[0051] Step 2 (Compare the differences): Compare the calculated theoretical predictions (i.e., theoretical values ​​of magnetic gradient tensor and total magnetic field strength) with the actual observed values ​​(i.e., observed values ​​of magnetic gradient tensor and total magnetic field strength) and calculate the differences between them (i.e., the residuals in the objective function).

[0052] Step 3 (Feedback Adjustment): If the difference is large, the guessed values ​​of the magnetic target position and magnetic moment are automatically adjusted by optimization algorithms (such as gradient descent or intelligent algorithms such as Cuckoo).

[0053] Step 4 (Iterative Convergence): Repeat steps 1 to 3, iterating continuously until the difference between the theoretical prediction and the actual observation is less than a certain threshold. At this point, the corresponding position and magnetic moment parameters are determined as the final processing result, and the position information included in the final processing result is the obtained position coordinates of the magnetic target.

[0054] In other words, the embodiments of this application establish a total field theoretical calculation model and a magnetic gradient tensor theoretical model based on the magnetic dipole physical model, which include the target position, magnetic moment, and the influence of the geomagnetic field. With the objective of minimizing the norm of the difference between the measured value and the theoretical prediction value, an iterative optimization algorithm (such as the Levenberg-Marquardt algorithm) is used to solve for the target position coordinates and magnetic moment vector that minimize the objective function. The solved target position coordinates are then used as the positioning result for the magnetic target.

[0055] The following three examples illustrate this point. Figure 2 Before introducing three examples, we will first explain how to identify the relevant parameters in each step.

[0056] Magnetic gradient tensor observations use magnetic gradient tensor information. Characterization and total magnetic field strength observations adopt the total field results. The geomagnetic field background observation values ​​are characterized by the three components of the Earth's magnetic field; the target physical models include the following formulas respectively: Example 1 (3) (as the total field theory calculation model) and Formula (4) (as the magnetic gradient tensor component model) or Example 2 (3) (as the total field theory calculation model) and Formula (13) (as the magnetic gradient tensor invariant model). The target physical model of Example 3 also uses Formula (3) and Formula (13). Unlike Example 1 and Example 2, the position vectors in the total field theory calculation model and the magnetic gradient tensor theory model in this scheme use different measurement point coordinates.

[0057] In Example 1, a set of hypothetical magnetic target position parameters and magnetic moment parameters includes: hypothetical magnetic target position parameters = the three-dimensional spatial coordinates of the magnetic target (x0, y0, z0), and hypothetical magnetic target magnetic moment parameters = the magnetic moment vector of the magnetic target. In Examples 2 and 3, a set of hypothetical magnetic target position parameters and magnetic moment parameters include: hypothetical magnetic target position parameter = distance R between the magnetic target and the measurement point, and hypothetical magnetic target magnetic moment parameter = magnetic moment modulus M of the magnetic target.

[0058] In Example 1, the theoretical predictions include: the theoretical value of the total magnetic field strength. and the theoretical value of the magnetic gradient tensor (A vector containing multiple independent components). In Example 2, the theoretical predictions include: the theoretical value of the total magnetic field strength. And the theoretical value of the magnetic gradient tensor (i.e., the theoretical value of the invariants). .

[0059] To achieve single-point localization of magnetic targets by integrating the total field, embodiments of this application require removing the Earth's magnetic field from the total magnetic field strength observations measured by the optically pumped magnetometer. Considering the relative stability of the Earth's magnetic field in local survey areas, the three-dimensional spatial coordinates of the magnetic target can be obtained iteratively using a three-component model of the magnetic dipole after acquiring the Earth's magnetic field through ground base stations, the International Geomagnetic Reference Field (IGRF) model, and total magnetic field strength observations in areas without magnetic anomalies. Assuming the three components of the Earth's magnetic field are:

[0060] (1)

[0061] Given the coordinates of the tensor measurement point Then, assume the current coordinates of the magnetic target are... , If is the position vector from the measuring point to the magnetic target, then the three-component magnetic field model of the magnetic dipole is as follows:

[0062] (2)

[0063] The total field results of the known optical pump measurement Based on the three components of the Earth's magnetic field and the three components of the magnetic dipole's magnetic field, the theoretical value of the total magnetic field strength at the optical pump measurement point can be determined. The total field theory calculation model, represented by the following formula 3, is as follows:

[0064] (3)

[0065] Example 1: Given the measured magnetic gradient tensor information Based on the magnetic moment of the magnetic dipole and the position vector from the measuring point to the magnetic target, the theoretical value of the magnetic gradient tensor at the measuring point can be determined. The magnetic gradient tensor component model is used to characterize it as follows:

[0066] (4)

[0067] According to formulas (2), (3), and (4), there are a total of 6 equations, and the unknown is the current coordinates of the magnetic target. Magnetic moment vector of a magnetic target There are also six unknowns, and single-point positioning can be achieved by solving the system of equations.

[0068] In the formula It is the position vector from the measuring point to the magnetic target, where These are the three-dimensional spatial coordinates of the magnetic target. R is the three-dimensional spatial coordinate of the measurement point; R is the magnitude of the position vector. Vacuum permeability; It is the magnetic moment vector of the magnetic target.

[0069] Objective function:

[0070] In other words, in some embodiments of this application, the magnetic gradient tensor theoretical model is the magnetic gradient tensor component model (i.e., formula (4)), and the magnetic gradient tensor component model is used to calculate the theoretical values ​​of multiple independent components of the magnetic gradient tensor; the construction of the objective function based on the difference between the theoretical prediction value and the corresponding observed value includes: based on the first difference between the multiple independent components of the observed magnetic gradient tensor and the corresponding theoretical value (i.e., ) and the second difference between the observed total magnetic field strength and the corresponding theoretical value (i.e. The objective function is constructed as follows. For example, in some embodiments of this application, the objective function is the weighted sum of squares or norm of the first difference and the second difference.

[0071] Example 2: Considering that the relevant equations in Example 1 require attitude projection to obtain the independent components of the magnetic gradient tensor, achieving single-point localization of magnetic targets requires expensive combined inertial navigation to provide attitude information, and the solution process is cumbersome, the following will implement single-point localization of magnetic targets based on tensor invariants and the total field.

[0072] First, the unit vectors of the magnetic moment vector and position vector from the magnetic target to the measurement point are obtained using the magnetic gradient tensor (i.e., the unit vectors of the magnetic moment direction and the position direction). Then, prior conditions are used to remove dummy solutions, such as the approximate directions of the position vector or magnetic moment vector, to obtain the true values. and .

[0073]

[0074] Assume R is the distance between the magnetic source and the measurement point. If it is the magnitude of the magnetic moment, then

[0075]

[0076] Its eigenvalues ​​are obtained by measuring the magnetic gradient tensor, and the magnitude of the magnetic moment is... Substituting the distance R between the magnetic source and the measurement point into the formula for calculating tensor invariants, we get:

[0077] (13)

[0078] By combining formulas (2), (3), and (13), with two unknowns and two equations, the magnitude of the magnetic moment can be solved. The distance R between the magnetic source and the measurement point. Therefore, positioning can be achieved based on the unit vectors of the magnetic moment vector and the position vector from the magnetic target to the measurement point.

[0079] In the above formula It is a vector of magnetic moment. It is the eigenvalue with the smallest absolute value corresponding to the full tensor magnetic gradient matrix. The corresponding feature vector, and These are the eigenvalues ​​of the corresponding full tensor magnetic gradient matrix. The eigenvectors. In Formula 2 These are the eigenvalues ​​of the full tensor magnetic gradient matrix, and , Where R is the vacuum permeability, and R is the distance between the magnetic source and the measurement point. It is the magnitude of the magnetic moment, where, It is a constant.

[0080] Objective function:

[0081] In other words, in some embodiments of this application, the magnetic gradient tensor theoretical model is a magnetic gradient tensor invariant model (i.e., the above formula (13)); before inputting a set of hypothetical magnetic target position parameters and magnetic moment parameters into the target physical model, the method further includes: performing feature decomposition on the magnetic gradient tensor observations to obtain eigenvalues ​​(λ1, λ2, λ3) and eigenvectors (V1, V2, V3); based on the eigenvalues ​​and eigenvectors, determining the unit vector of the position direction from the measurement point to the magnetic target to be located (i.e., r̃) and the unit vector of the magnetic moment direction of the magnetic target (i.e., m̃); wherein, the hypothetical magnetic target position parameters include the distance between the magnetic target and the measurement point (i.e., the distance R between the magnetic source and the measurement point as defined above), and the hypothetical magnetic target magnetic moment parameters include the magnetic moment modulus of the magnetic target (i.e., the modulus M of the magnetic moment as defined above); the theoretical prediction value includes: the theoretical invariant calculated by the invariant model based on the distance and the magnetic moment modulus. The magnitude (i.e., the right side of formula (13)) and the theoretical total field value calculated by the total field theoretical calculation model based on the distance, magnetic moment modulus, the direction unit vector and the observed value of the geomagnetic field background (i.e., the result corresponding to formula (3)); the construction of the objective function based on the difference between the theoretical predicted value and the corresponding observed value includes: constructing the objective function based on the difference between the invariant observed value calculated from the observed value of the magnetic gradient tensor (i.e., the left side of formula (13)) and the theoretical invariant value and the difference between the observed value of the total magnetic field strength and the theoretical total field value.

[0082] For example, in some embodiments of this application, the process of determining the position direction unit vector and the magnetic moment direction unit vector includes: performing feature decomposition on the magnetic gradient tensor observations to obtain multiple sets of candidate direction unit vectors and magnetic moment direction unit vector combinations; and selecting one set from the multiple sets of direction unit vectors and magnetic moment direction unit vector combinations as the position direction unit vector and the magnetic moment direction unit vector based on preset physical constraints.

[0083] Example 3: If there is a significant difference between the total field measurement point and the tensor measurement point, the distance deviation between the two cannot be ignored in the solution. It is necessary to modify the formulas for the three components and the total field according to the actual situation to obtain more accurate measurement results.

[0084] Given the coordinates of the total field measurement points Then, assume the current coordinates of the magnetic target are... If is the position vector from the measuring point to the magnetic target, then the three-component magnetic field model of the magnetic dipole is as follows:

[0085] (14)

[0086] In the formula, It is the three-dimensional position coordinate deviation between the total field measuring point and the tensor measuring point.

[0087] The total field results of the known optical pump measurement Based on the three components of the Earth's magnetic field and the three components of the magnetic dipole's magnetic field, the optical pumping measurement point can be determined. Total field theoretical value

[0088] (15)

[0089] Based on the corrected total field theoretical value, high-precision real-time positioning of a single magnetic target can be achieved by following Example 1 or Example 2.

[0090] Initial value solution scheme: After neglecting the angle between the Earth's magnetic field and the magnetic field of the magnetic target at the measurement point, the optical pumping measurement results from the magnetic anomaly region and the non-anomaly region are subtracted to obtain an approximate value of the total field of the magnetic target at that measurement point. Thus, the magnitude of the magnetic moment can be obtained using traditional algorithms. An approximate solution for the distance R between the magnetic source and the measurement point. The solution method is as follows:

[0091]

[0092] According to formulas (13), (16) and (17), the distance R between the magnetic source and the measurement point can be solved by the ratio method, and then according to the tensor invariant... The magnitude of the magnetic moment can be calculated. After the solution is completed, it can be substituted as the initial value for the exact solution into the solution equation for the tensor invariants to improve the convergence speed.

[0093] It is the angle between the magnetic dipole position vector and the magnetic moment vector. and These are the unit vectors for the position vector and the magnetic moment vector, respectively. It represents the total magnetic field of the target at the measuring point, excluding the Earth's magnetic field.

[0094] In other words, in Example 3, the observed values ​​of the total magnetic field strength and the observed values ​​of the magnetic gradient tensor are obtained at the first measurement point and the second measurement point, respectively, and the first measurement point and the second measurement point are different in space; when establishing the target physical model, the total field theory calculation model is constructed based on the positional relationship of the first measurement point relative to the magnetic target, and the magnetic gradient tensor theory model is constructed based on the positional relationship of the second measurement point relative to the magnetic target.

[0095] The differences between Examples 1, 2, and 3 above lie in the different target theoretical models and the different observations used in the objective function. In Example 1, the complete total field model (Equation (3)) and the complete magnetic gradient tensor component model (Equation (4) with 5 independent components) are used as the target physical model; the objective function simultaneously includes the total field residual and the residuals of the 5 tensor components (or some combination thereof); the 6 parameters (x0, y0, z0, m) are directly optimized. x ,m y ,m z Example 2 uses the total field model (Equation (3)) and the magnetometry tensor invariant model (Equation (13)) as the target physical model. In Example 2, the direction unit vector is first calculated using the magnetic gradient tensor observations (Equations (5)-(10)), and then the distance R and magnetic moment modulus M are solved using the total field theoretical calculation model and the magnetic gradient tensor invariant model. The objective function can include a combination of the total field residual invariant residuals. The optimization variables are R and M (2 parameters), and then the position and magnetic moment vector are obtained by combining the direction unit vector. The difference between Example 3 and Example 1 and Example 2 is that this example is used to correct the positional deviation between the total field measurement point and the tensor measurement point, that is, the position vector in the total field theoretical calculation model and the magnetic gradient tensor component model (or the magnetic gradient tensor invariant model) uses different measurement point coordinates. The objective function is constructed accordingly based on the model used (Example 1 or Example 2). The optimization solution is performed based on the model used.

[0096] like Figure 3 As shown, some embodiments of this application provide a magnetic target positioning device. It should be understood that this device is similar to the one described above. Figure 2Corresponding to the method embodiments, it can execute the various steps involved in the above method embodiments. The specific functions of the device can be found in the description above. To avoid repetition, detailed descriptions are appropriately omitted here. The device includes at least one software function module that can be stored in the memory or embedded in the device's operating system in the form of software or firmware. The magnetic target positioning device includes: an observation value acquisition module 310, a target physical model construction module 320, a theoretical prediction value acquisition module 330, an objective function construction module 340, and a magnetic target position output module 350.

[0097] The observation acquisition module is configured to acquire magnetic field property observations of the area where the magnetic target to be located is located, wherein the observations include: magnetic gradient tensor observations, total magnetic field strength observations, and geomagnetic field background observations.

[0098] The target physics model construction module is configured to build a target physics model based on the magnetic dipole model. The target physics model includes a total field theory calculation model and a magnetic gradient tensor theory model. The total field theory calculation model takes the position parameters and magnetic moment parameters of the magnetic target and the background information of the geomagnetic field as inputs. The magnetic gradient tensor theory model includes a magnetic gradient tensor component model or a magnetic gradient tensor invariant model.

[0099] The theoretical prediction value acquisition module is configured to input a set of hypothetical magnetic target position parameters and magnetic moment parameters into the target physical model to obtain theoretical prediction values, wherein the theoretical prediction values ​​include theoretical values ​​of magnetic gradient tensor and theoretical values ​​of total magnetic field strength.

[0100] The objective function construction module is configured to construct an objective function based on the difference between the theoretical prediction and the corresponding observed value.

[0101] The magnetic target position output module is configured to adjust the assumed magnetic target position parameters and magnetic moment parameters through an optimization algorithm to minimize the objective function, and use the parameter values ​​corresponding to the minimization as the position coordinates of the magnetic target.

[0102] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the device described above can be referred to the corresponding process in the aforementioned method, and will not be elaborated further here.

[0103] Some embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed, can implement the magnetic target positioning method as described in any of the above embodiments.

[0104] Some embodiments of this application provide a magnetic target positioning system, including: a data acquisition unit (located in the data acquisition layer), configured to acquire and transmit observations of magnetic field properties of the area where the magnetic target to be located is located, wherein the observations include: magnetic gradient tensor observations, total magnetic field strength observations, and geomagnetic field background observations; and a host computer for receiving the observations, including a processor and a memory, wherein the memory stores a computer program, and when the program is executed by the processor, it can implement the magnetic target positioning method as described in any of the above embodiments.

[0105] like Figure 4 As shown, some embodiments of this application also provide an electronic device 400, which can serve as a host computer and includes, for example, a memory 410, a processor 420, and a computer program stored in the memory 410 and executable on the processor 420. When the processor 420 reads and executes the computer program via a bus 430, it can implement the magnetic target positioning method as described in the above embodiments.

[0106] Processor 420 can process digital signals and may include various computing architectures. For example, it may be a complex instruction set computer architecture, a reduced instruction set computer architecture, or an architecture that implements multiple instruction set combinations. In some examples, processor 420 may be a microprocessor.

[0107] Memory 410 can be used to store instructions executed by processor 420 or data related to the execution of instructions. These instructions and / or data may include code used to implement some or all of the functions of one or more modules described in the embodiments of this application. The processor 420 of the embodiments of this disclosure can be used to execute the instructions in memory 410 to implement… Figure 2 The method shown. Memory 410 includes dynamic random access memory, static random access memory, flash memory, optical memory, or other memory well known to those skilled in the art.

[0108] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0109] In addition, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0110] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0111] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application. It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0112] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0113] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A method for locating a magnetic target, the method comprising: Obtain the observed magnetic field properties of the area where the magnetic target to be located is located, wherein the observed magnetic field properties include: observed magnetic gradient tensor, observed total magnetic field strength, and observed geomagnetic field background. A target physical model is established based on the magnetic dipole model, wherein the target physical model includes a total field theory calculation model and a magnetic gradient tensor theory model, and the total field theory calculation model takes the observed values ​​of the geomagnetic field background as an input; A set of hypothetical magnetic target position parameters and magnetic moment parameters are input into the target physical model to obtain theoretical prediction values, wherein the theoretical prediction values ​​include theoretical values ​​of magnetic gradient tensor and theoretical values ​​of total magnetic field strength. An objective function is constructed based on the difference between the theoretical predictions and the corresponding observed values; The position coordinates of the magnetic target are obtained by adjusting the assumed position parameters and magnetic moment parameters of the magnetic target through an optimization algorithm to minimize the objective function.

2. The magnetic target positioning method as described in claim 1, characterized in that, The total magnetic field strength observation value is used to characterize the total magnetic field strength of the Earth's magnetic field and the magnetic field generated by the magnetic target at the measurement point location. The magnetic gradient tensor observation value is used to characterize the rate of change of the magnetic field vector in space at the measurement point location. The geomagnetic field background observation value is used to characterize the magnetic field vector generated by the Earth's magnetic field when the magnetic target is not present at the measurement point location.

3. The magnetic target positioning method as described in any one of claims 1-2, characterized in that, The magnetic gradient tensor theoretical model is a magnetic gradient tensor component model. The magnetic gradient tensor component model is used to calculate the theoretical values ​​of multiple independent components of the magnetic gradient tensor. The total field theoretical calculation model is used to calculate the theoretical value of the total magnetic field strength. The objective function constructed based on the difference between the theoretical prediction and the corresponding observed value includes: The objective function is constructed based on the first difference between the multiple independent components of the observed magnetic gradient tensor and the theoretical values ​​of the corresponding independent components, and the second difference between the observed total magnetic field strength and the corresponding theoretical value.

4. The magnetic target positioning method as described in claim 3, characterized in that, The objective function is the weighted sum of squares or norm of the first difference and the second difference.

5. The magnetic target positioning method as described in any one of claims 1-2, characterized in that, The magnetic gradient tensor theoretical model is a magnetic gradient tensor invariant model; Before inputting a set of hypothetical magnetic target position parameters and magnetic moment parameters into the target physical model, the method further includes: performing eigenvalue decomposition on the magnetic gradient tensor observations to determine the unit vector of the position direction from the measurement point to the magnetic target and the unit vector of the magnetic moment direction of the magnetic target; wherein, the hypothetical magnetic target position parameters include the distance between the magnetic target and the measurement point, and the hypothetical magnetic target magnetic moment parameters include the magnetic moment modulus of the magnetic target; the theoretical prediction values ​​include: theoretical invariant values ​​calculated by the magnetic gradient tensor invariant model based on the distance and the magnetic moment modulus, and theoretical total field values ​​calculated by the total field theory calculation model based on the geomagnetic field background observations; the step of constructing an objective function based on the difference between the theoretical prediction values ​​and the corresponding observation values ​​includes: constructing the objective function based on the difference between the invariant observation values ​​calculated from the magnetic gradient tensor observations and the theoretical invariant values, and the difference between the total magnetic field strength observation values ​​and the theoretical total field values.

6. The magnetic target positioning method as described in claim 5, characterized in that, The step of performing eigenvalue decomposition on the magnetic gradient tensor observations to determine the unit vector of the position direction from the measurement point to the magnetic target and the unit vector of the magnetic moment direction of the magnetic target includes: The magnetic gradient tensor observations are decomposed to obtain multiple sets of candidate combinations of direction unit vectors and magnetic moment direction unit vectors. Based on preset physical constraints, one set is selected from the multiple sets of combinations of direction unit vectors and magnetic moment direction unit vectors as the position direction unit vector and the magnetic moment direction unit vector.

7. The magnetic target positioning method as described in any one of claims 1-2, characterized in that, The observed values ​​of the total magnetic field strength and the observed values ​​of the magnetic gradient tensor are obtained at the first measurement point and the second measurement point, respectively. When establishing the target physical model, the total field theoretical calculation model is constructed based on the positional relationship of the first measurement point relative to the magnetic target, and the magnetic gradient tensor theoretical model is constructed based on the positional relationship of the second measurement point relative to the magnetic target.

8. A magnetic target positioning device, characterized in that, The magnetic target positioning device includes: The observation acquisition module is configured to acquire observation values ​​of the measurement area where the magnetic target to be located is located, wherein the observation values ​​include: magnetic gradient tensor observation values, total magnetic field strength observation values, and geomagnetic field background observation values; The target physics model construction module is configured to build a target physics model based on the magnetic dipole model, wherein the target physics model includes a total field theory calculation model and a magnetic gradient tensor theory model, and the total field theory calculation model takes the geomagnetic field background observation value as an input; The theoretical prediction value acquisition module is configured to input a set of hypothetical magnetic target position parameters and magnetic moment parameters into the target physical model to obtain theoretical prediction values, wherein the theoretical prediction values ​​include theoretical values ​​of magnetic gradient tensor and theoretical values ​​of total magnetic field strength; The objective function construction module is configured to construct an objective function based on the difference between the theoretical prediction value and the corresponding observed value. The magnetic target position output module is configured to adjust the assumed magnetic target position parameters and magnetic moment parameters through an optimization algorithm to minimize the objective function and obtain the position coordinates of the magnetic target.

9. A computer-readable storage medium having a computer program stored thereon, said computer program being executed to implement the magnetic target positioning method as described in any one of claims 1-7.

10. A magnetic target positioning system, comprising: The data acquisition unit is configured to acquire and transmit the magnetic field property observation values ​​of the area where the magnetic target to be located is located, wherein the observation values ​​include: magnetic gradient tensor observation values, total magnetic field strength observation values, and geomagnetic field background observation values. A host computer, used to receive the observation values, includes a processor and a memory, wherein the memory stores a computer program, and when the program is executed by the processor, it can implement the magnetic target positioning method as described in any one of claims 1-7.

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