A multi-target positioning method and system based on magnetic measurement

Abstract

The application provides a multi-target positioning method and system based on magnetic measurement, a magnetic gradient tensor system collects magnetic gradient tensor elements above a target and normalized magnetic source strength NSS generated by multiple targets, a coordinate system is established to set a solution space, the solution space is divided, a magnetic dipole exists at each grid point in the solution space, the normalized magnetic source strength obtained in the collecting step is vectorized, and linear equations between the normalized magnetic source strength and the grid magnetic dipole magnetic moment module are established by combining data of multiple collecting points. Only the magnetic dipole magnetic moment module value of the grid point corresponding to the target is not 0, and the magnetic moment module values of other magnetic dipoles are equal to 0, the L1 norm minimization method is used to estimate the size and position of the non-0 magnetic moment in the solution space, the number of non-0 magnetic moments is equal to the number of targets, and the module value of the non-0 magnetic moment corresponds to the magnetic moment vector module of the target. The multi-target positioning method does not need to estimate the number of targets in advance.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of target detection, and particularly relates to a multi-target positioning method and system based on magnetic measurement. BACKGROUND

[0002] Magnetic measurement is an important non-destructive target detection method, and has important applications in the fields of underground pipelines, underground / submarine metal targets and resource exploration. Influenced by geomagnetic field induction magnetization, a ferromagnetic target generates an induced magnetic field, resulting in distortion of the low magnetic field near the target. By collecting the magnetic field above the target, the position, attitude and other information of the target can be inverted to realize target detection and identification.

[0003] The existing magnetic target positioning method is generally based on the assumption of a single target. When there are multiple targets with proximal distribution, the magnetic anomaly field generated by the targets is superimposed, and based on the traditional magnetic target positioning method, there are problems: (1) the number of targets cannot be determined; (2) the inverted target position is different from the real position, and the positioning error is large. For the problem of multi-target detection, the number of targets is generally needed as prior information, and then the three-dimensional positions of all targets are estimated. SUMMARY

[0004] The application provides a multi-target positioning method and system based on magnetic measurement to solve the problems in the background art.

[0005] To solve the above technical problems, the application discloses a multi-target positioning method based on magnetic measurement, which comprises the following steps:

[0006] a. Setting and sectioning step: establishing a coordinate system to set a solution space, and sectioning the solution space,

[0007] b. Acquisition step: acquiring magnetic gradient tensor elements above the target and normalized magnetic source strength NSS generated by multiple targets;

[0008] c. Data processing step: constructing a point magnetic dipole model based on the solution space, inputting the acquired magnetic gradient tensor elements and magnetic source strength NSS into the point magnetic dipole model, and outputting the size and position of the non-0 magnetic moment to realize target positioning.

[0009] Further, the point magnetic dipole model comprises multi-magnetic dipole parameter solving based on L1 norm minimization:

[0010]

[0011] wherein ‖·‖1 represents L1 norm, is a magnetic moment module parameter vector of the magnetic dipole.

[0012] Further, the solution algorithm of the L1 norm minimization includes the basis pursuit algorithm, the interior point method, the simplex method or the orthogonal matching pursuit algorithm and the primal-dual interior point method.

[0013] Further, in the data processing step, the solving space is divided, and the distance between the control magnetic field sensor and the target is required to be greater than 2.5 times the maximum size of the grid.

[0014] Further, in the setting and dividing step, the solving space is a cuboid.

[0015] Further, in the collecting step, a observation horizontal plane is selected above the target, and the magnetic gradient tensor elements B xx , B xy , B xz , B yx , B yz are uniformly collected at the observation horizontal plane by using the magnetic gradient tensor system.

[0016] Further, the data processing step includes vectorizing the normalized magnetic source intensity collected on the observation horizontal plane, combining the data of multiple collection points on the observation horizontal plane, and establishing a linear equation group:

[0017]

[0018] s=Ψτ

[0019] Wherein, Ψ is a P*Q matrix, r ij (i=1,2,…,P,j=1,2,…,Q) is the distance between the ith observation point on the observation horizontal plane and the jth magnetic dipole in the solving space. By solving the linear equation group, the magnetic moment module distribution τ of the magnetic dipole in the solving space can be determined.

[0020] Preferably, the total number of sampling points is P=lenx*leny, wherein lenx is the number of sampling points along the x direction, and leny is the number of sampling points along the y direction.

[0021] The second aspect of the present application discloses a multi-target positioning system based on magnetic measurement, comprising:

[0022] a. A collecting module for collecting magnetic gradient tensor elements above the target and normalized magnetic source intensity NSS generated by multiple targets;

[0023] b. A data processing module for determining the normalized magnetic source intensity NSS generated by multiple targets according to the collected magnetic gradient tensor field, simplifying to a point-like magnetic dipole model when the distance between the magnetic field sensor and the target is greater than 2.5 times the maximum size of the known target, and when the number of non-zero magnetic dipoles n in the solving space, the position of the ith magnetic dipole is (x i ,y iz i ), the magnetic moment module value is m i , n magnetic dipoles generate total normalized magnetic source intensity and establish a coordinate system to set up a solution space for partitioning, and the normalized magnetic source intensity collected on the observation plane is vectorized as s=[NSS1, NSS2, …, NSS P ] T , a linear equation group between the normalized magnetic source intensity and the grid magnetic dipole magnetic moment module is established:

[0024]

[0025] s=Ψτ

[0026] wherein Ψ is a P×Q matrix, r ij (i=1, 2, …, P, j=1, 2, …, Q) is the distance between the ith observation point on the observation plane and the jth magnetic dipole in the solution space. By solving the linear equation group, the magnetic moment module distribution τ of the magnetic dipole in the solution space is determined, and the size and position of the non-0 magnetic moment in the solution space are solved by using the L1 norm minimization method.

[0027] Further, the acquisition module includes a sensor array for acquiring five magnetic gradient tensor elements B xx , B xy , B xz , B yx , B yz and normalized magnetic source intensity NSS generated by multiple targets, the five magnetic gradient tensor elements satisfy the formula wherein B ij (i, j=x, y, z) is the magnetic gradient tensor element generated by the dipole, B i is the ith component of the magnetic induction intensity, r j is the jth component of the distance vector between the observation point where the magnetic field sensor is located and the target position, and the normalized magnetic source intensity NSS generated by multiple targets satisfies the formula wherein n is the number of non-0 magnetic dipoles in the solution space, (x i , y i , z i ) is the position of the ith magnetic dipole, and the magnetic moment module value is m i .

[0028] Further, the system can realize multi-target positioning without pre-estimating the number of targets, and the system further includes a user interface module for displaying the position and size of the non-0 magnetic moment and the number of targets.

[0029] Preferably, the system further includes a calibration module for calibrating the sensors of the acquisition module to improve the measurement accuracy.

[0030] Preferably, the system further comprises a data storage module for storing the collected magnetic gradient tensor field data, the collected normalized magnetic source strength NSS, the solved position and size of the non-0 magnetic moment, and the like.

[0031] Compared with the prior art, the application provides a multi-target positioning method based on magnetic measurement, which has the following beneficial effects:

[0032] (1) The application innovatively provides a multi-target positioning method based on magnetic measurement. The magnetic gradient tensor system collects the magnetic gradient tensor elements above the target to determine the normalized magnetic source strength NSS generated by the target. A coordinate system is established to set a solving space, and the solving space is divided. Each grid point in the solving space has a magnetic dipole. Therefore, the normalized magnetic source strength obtained in the collection step is vectorized, and the data of multiple collection points are combined to establish a linear equation set between the normalized magnetic source strength and the grid magnetic dipole magnetic moment module.

[0033] (2) Based on the sparse distribution of non-0 magnetic dipoles in the solving space, only the magnetic dipole magnetic moment module value corresponding to the grid point where the target is located is non-0, and the magnetic moment module values of other magnetic dipoles are equal to 0. The L1 norm minimization method is used to estimate the size and position of the non-0 magnetic moment in the solving space. The number of non-0 magnetic moments is equal to the number of targets, and the module value of the non-0 magnetic moment corresponds to the magnetic moment vector module of the target. This multi-target positioning method does not need to estimate the number of targets in advance. BRIEF DESCRIPTION OF DRAWINGS

[0034] The application will be further described below in combination with the drawings and examples.

[0035] Figure 1 is the magnetic anomaly field generated by the target in the position adjacent to the target, which is mixed;

[0036] Figure 2 is the position distribution of the multiple targets in the solving space;

[0037] Figure 3 is the observed plane magnetic gradient tensor field (unit: nT / m);

[0038] Figure 4 is the observed plane normalized magnetic source strength (unit: nT / m);

[0039] Figure 5 is the linear equation set solution τ. DETAILED DESCRIPTION

[0040] In an exemplary embodiment of the application,

[0041] Firstly, the magnetic anomaly field generated by a ferromagnetic target is introduced. When the distance between the magnetic field sensor and the target is greater than 2.5 times the maximum size of the target, the target can be simplified into a point magnetic dipole model. The magnetic dipole model is characterized by a three-dimensional magnetic moment vector and a three-dimensional position vector, and the magnetic anomaly field generated by the target is

[0042]

[0043] where μ0=4π×10 -7 H / m is the permeability of air, is a three-dimensional magnetic moment vector, is the distance vector between the observation point where the magnetic field sensor is located and the target position, and r is the modulus of the distance vector. Thus, the magnetic gradient tensor field generated by the target can be determined In the rectangular coordinate system, G is a second-order tensor:

[0044]

[0045] The magnetic gradient tensor matrix G is a symmetric matrix, and the trace of the matrix is 0, so there are only five independent elements of the magnetic gradient tensor, including two diagonal elements and three non-diagonal elements. The calculation method of the magnetic gradient tensor elements B ij (i,j=x,y,z) generated by the magnetic dipole is as follows:

[0046]

[0047] where only when i,j is the same, δ ij =1, and in other cases, δ ij =0. r i is the i component of the distance vector , and m i is the i component of the magnetic moment vector . The normalized source strength NSS of the target, μ, is a scalar quantity independent of the direction of the target magnetic moment vector, which is only related to the modulus m of the magnetic moment vector and the distance r. At the same time, the normalized source strength μ of the magnetic dipole can be determined by the three eigenvalues λ1, λ2, λ3 of the magnetic gradient tensor matrix G, and the calculation formula is as follows:

[0048]

[0049] Therefore, by collecting the magnetic gradient tensor field above the target, determining the magnetic gradient tensor matrix G, and calculating the eigenvalues, the normalized source strength NSS of the target can be determined.

[0050] Secondly, the multi-target positioning method is introduced. For example Figure 1 ​As shown, there are two close ferromagnetic targets 1 and 2 in the underground space. Under the action of the geomagnetic field induced magnetization, the targets will generate magnetic anomaly fields. Curve 1 corresponds to the magnetic anomaly field generated by only target 1, curve 2 corresponds to the magnetic anomaly field generated by only target 2, and the uppermost curve is the real magnetic anomaly field collected by the magnetic field sensor along a horizontal side line, which is the result of superposition of curve 1 and curve 2. It can be seen that the magnetic anomaly fields generated by the two adjacent targets are mixed, and the number of targets cannot be determined from the measured magnetic anomaly field curve.

[0051] A rectangular coordinate system 0-xyz is established, and the ground is the xoy plane, so that the space where the target is located is the space of z<0. A rectangular solving space is set to ensure that all ferromagnetic targets are in the solving space, as shown. Figure 2 The solving space is uniformly divided, and the number of grid divisions is Q=nx×ny×nz. It is assumed that there is a magnetic dipole at each grid point in the solving space, and the magnetic moment of the magnetic dipole at the grid point without the target is 0, and the magnetic moment modulus of the magnetic dipole corresponding to the grid point with the target is non-0. When the number of non-0 magnetic dipoles in the solving space is n, the position of the i-th magnetic dipole is (x i ,y i ,z i ), and the magnetic moment modulus is m i , and the total normalized magnetic source intensity generated by the n magnetic dipoles is:

[0052]

[0053] A selected observation horizontal plane is selected above the target, and the magnetic gradient tensor system is used to uniformly collect the magnetic gradient tensor elements B xx , B xy , B xz , B yx , B yz at the observation plane to establish a magnetic gradient tensor matrix, and the total number of sampling points of the observation plane is P=lenx*leny, wherein lenx is the number of sampling points along the x direction, and leny is the number of sampling points along the y direction. According to formula (4), the total normalized magnetic source intensity NSS can be collected on the observation plane, and the normalized magnetic source intensity vector s=[NSS1,NSS2,…,NSS P ] T The data of multiple collection points on the observation plane are combined to establish a linear equation group:

[0054]

[0055] s=Ψτ

[0056] Wherein, Ψ is a P×Q matrix, and r ij(i = 1, 2, …, P, j = 1, 2, …, Q) is the distance between the i-th observation point on the observation plane and the j-th magnetic dipole in the solving space. By solving the linear equation set, the magnetic moment module distribution τ of the magnetic dipole in the solving space can be determined.

[0057] Finally, a multi-magnetic dipole parameter solving method based on L1 norm minimization is given. The solution τ of the linear equation set corresponds to the magnetic moment module of the Q magnetic dipoles in the solving space. Only the magnetic moment of the magnetic dipole at the position of the target is non-zero, and the magnetic moment of the magnetic dipole at the remaining grid positions is equal to 0. Therefore, the equation set (6) is a sparse solving problem, and the method based on L1 norm minimization is used to determine τ.

[0058]

[0059] wherein ‖·‖1 represents the L1 norm, is the magnetic moment module parameter vector of the magnetic dipole. There are various solving algorithms for L1 norm minimization, such as basis pursuit algorithm, interior point method, simplex method, orthogonal matching pursuit algorithm, etc. Here, the primal-dual interior point method is used to solve τ. According to the number of non-zero solutions, the number of targets can be determined, and the three-dimensional positions of all targets can be determined according to the positions of the non-zero solutions.

[0060] The positioning results of the above embodiments are detected by simulation analysis: the simulation experiment is set as follows: the geomagnetic field strength is 55000 nT, the geomagnetic inclination is 57.58°, and the geomagnetic declination is -5.14°. Two ferromagnetic targets close in position are buried in the underground space, target 1 is located at (9, 10, -2) m, and the magnetic dipole moment is (0, 4, 0) Am 2 , and target 2 is located at (9.5, 10, -2) m, and the magnetic dipole moment is (1, 2, -5) Am 2 .

[0061] The magnetic gradient tensor elements above the target are collected, the observation plane is a 20m×20m horizontal plane, the height from the ground is 1m, the sampling interval in x and y directions is 1m, and the number of sampling points is P = 441. The collected magnetic gradient element distribution is as shown in Figure 3 . The normalized magnetic source strength NSS on the observation plane is as shown in Figure 4 . It can be seen from the figure that the magnetic anomaly fields generated by the two ferromagnetic targets are overlapped, and the number of targets cannot be directly determined.

[0062] Based on the multi-target positioning method proposed in the present patent, a solving space of 20m×20m×3m is set. The solving space is uniformly divided, and the length of the divided grid is 0.5m, and there are 11767 grid nodes. According to the normalized magnetic source strength NSS distribution on the observation plane, the primal-dual interior point method is used to solve the magnetic moment module value distribution τ of the magnetic dipole in the underground space, as shown in Figure 5The non-0 elements are 2, and the number of targets in the underground space is 2. According to the positions of the non-0 elements, the three-dimensional positions of the targets are obtained, and the results are (9, 10, -2) m and (9.5, 10, -2) m. Therefore, in the case of no noise, the multi-target positioning result proposed in the patent is consistent with the theoretical positioning result of the target.

[0063] In an exemplary embodiment of the present application, the embodiment introduces a multi-target positioning system based on magnetic measurement, which can efficiently and accurately realize the positioning of multiple targets. The system mainly includes a collection module, a data processing module, a user interface module, a calibration module and a data storage module. The functions of each module and its application in the system will be described in detail below.

[0064] The module includes:

[0065] a. The collection module is the core input part of the system, which is used to collect the magnetic gradient tensor elements above the target and the normalized magnetic source strength NSS generated by multiple targets; and is used to collect a sensor array of five magnetic gradient tensor elements B xx , B xy , B xz , B yx , B yz and the normalized magnetic source strength NSS generated by multiple targets, wherein the five magnetic gradient tensor elements satisfy the formula where B ij (i,j=x,y,z) is the magnetic gradient tensor element generated by a dipole, B i is the i component of the magnetic induction intensity, r j is the j component of the distance vector of the observation point of the magnetic field sensor and the target position, and the normalized magnetic source strength NSS generated by multiple targets satisfies the formula where n is the number of non-0 magnetic dipoles in the solution space, (x i , y i , z i ) is the position of the i-th magnetic dipole, and the magnetic moment module value is m i . In actual operation, the sensor array is arranged on the observation plane, and the required magnetic gradient tensor elements and NSS values are obtained by accurate measurement, which provides basic data for subsequent data processing.

[0066] b. The data processing module is the core processing part of the system, which is used to determine the normalized magnetic source strength NSS generated by multiple targets according to the collected magnetic gradient tensor field. When the distance between the magnetic field sensor and the target is greater than 2.5 times the maximum size of the known target, it is simplified to a point-like magnetic dipole model. When the number of non-0 magnetic dipoles in the solution space n is solved, the position of the i-th magnetic dipole is (x i , yi z i ), the magnetic moment module is m i , n magnetic dipoles generate the total normalized magnetic source strength and establish a coordinate system to set up the solution space for subdivision, and the normalized magnetic source strength vector s collected on the observation plane is s = [NSS1, NSS2, …, NSS P ] T , a linear equation group between the normalized magnetic source strength and the grid magnetic dipole magnetic moment module is established:

[0067]

[0068] s = Ψτ

[0069] wherein Ψ is a P × Q matrix, r ij (i = 1, 2, …, P, j = 1, 2, …, Q) is the distance between the i th observation point on the observation plane and the j th magnetic dipole in the solution space, by solving the linear equation group, the magnetic moment module distribution τ of the magnetic dipole in the solution space is determined, and the size and position of the non-zero magnetic moment in the solution space are solved by using the L1 norm minimization method.

[0070] c. User interface module, for displaying the position and size of the non-zero magnetic moment, and the number of targets, through the intuitive graphical interface, the user can conveniently view the positioning result, and can perform subsequent operation according to the need.

[0071] d. Calibration module, for calibrating the sensor of the acquisition module to improve the measurement accuracy; in actual application, the sensor may deviate due to environmental factors or long-term use, and through the calibration module, the accuracy of the sensor can be ensured, so as to improve the positioning accuracy of the whole system.

[0072] e. Data storage module, for storing the collected magnetic gradient tensor field data, the collected normalized magnetic source strength NSS, the position and size of the non-zero magnetic moment solved, and other information. Through the data storage module, the user can conveniently query the historical data, and further analyze and process.

[0073] In the system application example, it is assumed that in a certain underground detection task, the positions and sizes of multiple unknown metal objects need to be determined. At this time, the multi-target positioning system based on magnetic measurement described in the embodiment can be used.

[0074] Firstly, the sensor array is arranged on the observation plane by the acquisition module, and the required magnetic gradient tensor elements and NSS values are collected. Then, the data processing module is used to process the collected data to solve the position and magnetic moment module of the non-zero magnetic dipole. Finally, the positioning result is displayed through the user interface module, and subsequent operation can be performed according to the need.

[0075] In practical applications, the system shows good stability and accuracy, and successfully realizes the positioning of multiple targets. At the same time, with the support of the calibration module and the data storage module, the measurement accuracy and data processing capacity of the system are further improved.

[0076] In summary, the multi-target positioning system based on magnetic measurement has wide application prospects and important practical significance.

[0077] Further, a multi-target positioning system based on magnetic measurement includes: when a calibration module calibrates a sensor of a collection module, obtaining output information of the sensor, and performing cross verification according to the output information to determine whether the sensor needs to be calibrated, and obtaining a preliminary calibration analysis result; performing preliminary self-calibration according to the preliminary calibration analysis result, when the preliminary calibration analysis result is that the sensor needs to be calibrated, performing software self-calibration on the sensor respectively, then reobtaining the output information based on the sensor after the software self-calibration, and performing secondary cross verification according to the output information to determine whether the sensor needs to be calibrated, and obtaining a secondary calibration analysis result; performing secondary self-calibration according to the secondary calibration analysis result, when the secondary calibration analysis result is that the sensor does not need to be calibrated, completing calibration of the sensor, when the secondary calibration analysis result is that the sensor needs to be calibrated, performing hardware self-calibration on the sensor respectively, then reobtaining the output information based on the sensor after the hardware self-calibration, and performing again cross verification according to the output information to determine whether the sensor needs to be calibrated, and obtaining again calibration analysis result; performing abnormal reminding according to the again calibration analysis result, when the again calibration analysis result is that the sensor does not need to be calibrated, completing calibration of the sensor, when the again calibration analysis result is that the sensor needs to be calibrated, performing abnormal reminding on the sensor. The above technical solution realizes calibration of the sensor through the calibration module, reduces errors of sensor sensing and collecting data, improves accuracy of the collection module in collecting magnetic gradient tensor elements above the target and normalized magnetic source strength NSS generated by multiple targets, so that the data processing module can analyze based on more accurate collected data of the magnetic gradient tensor elements above the target and the normalized magnetic source strength NSS generated by multiple targets, provides guarantee for analysis and processing of the data processing module, effectively improves accuracy of the multi-target positioning system based on magnetic measurement, and guarantees accuracy of the size and position of the non-0 magnetic moment in space. Through software self-calibration and hardware self-calibration, calibration is gradually performed, so that the sensor can be calibrated based on self-calibration without the need for relevant personnel to manually process, unnecessary trouble is reduced, time occupied by sensor calibration is also reduced, efficiency of the calibration module in calibrating the sensor of the collection module is improved, and through obtaining of the again calibration analysis result, calibration effect can be determined, guaranteeing that the calibrated sensor has high accuracy, and when necessary, abnormal reminding is performed to enable relevant personnel to assist in calibration, ensuring calibration effect of the calibration module on the sensor of the collection module.

[0078] When the data storage module stores the collected magnetic gradient tensor field data, the collected normalized magnetic source strength NSS, and the position and size information of the non-0 magnetic moment obtained by solving, the effectiveness of the collected magnetic gradient tensor field data, the collected normalized magnetic source strength NSS, and the position and size information of the non-0 magnetic moment obtained by solving is verified respectively to obtain an effectiveness verification result, and when the effectiveness verification result is passed, the collected magnetic gradient tensor field data, the collected normalized magnetic source strength NSS, and the position and size information of the non-0 magnetic moment obtained by solving are respectively encrypted to obtain first encrypted information, second encrypted information, and third encrypted information, then the first encrypted information, the second encrypted information, and the third encrypted information are subjected to data attribute matching to obtain a data matching result, and the data information is stored according to the data matching result. The above-mentioned effectiveness verification avoids invalid storage of data information when the data storage module stores the collected magnetic gradient tensor field data, the collected normalized magnetic source strength NSS, and the position and size information of the non-0 magnetic moment obtained by solving, reduces the space occupation of invalid information on the storage module, provides the security of the data storage module through encryption processing, avoids easy destruction of information in the data storage module, and at the same time, through data attribute matching of the first encrypted information, the second encrypted information, and the third encrypted information, the order of the stored information is ensured, data confusion is avoided, and the data storage module is not disordered, so that the data storage module can better store data information, and convenient information calling of the data storage module is provided.

[0079] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. If these modifications and variations of the present application belong to the scope of the claims of the present application and the same technology, the present application also intends to include these modifications and variations.

Claims

1. A multi-target locating method based on magnetic measurement, comprising the following steps: a. setting and partitioning steps: setting a coordinate system to establish a solution space, and partitioning the solution space; b. acquisition step: acquiring magnetic gradient tensor elements above the target and normalized magnetic source strength NSS generated by multiple targets; c. data processing step: constructing a point magnetic dipole model based on the solution space, inputting the acquired magnetic gradient tensor elements and magnetic source strength NSS into the point magnetic dipole model, and outputting the size and position of non-0 magnetic moment to realize target locating; The method comprises the following steps: collecting magnetic gradient tensor elements of a target; and determining the target's magnetic gradient tensor elements. 、 、 、 、 ; the point magnetic dipole model comprises multi-magnetic dipole parameter solving based on L1 norm minimization; , ； wherein, denotes the L1 norm, is a magnetic moment modulus parameter vector of the magnetic dipole. the data processing step comprises vectorizing the normalized magnetic source strength acquired on the observation plane, combining the data of multiple acquisition points on the observation plane, and establishing a linear equation set: wherein, is a matrix, is the distance between the i-th observation point on the observation plane and the j-th magnetic dipole in the solving space, and the magnetic moment module distribution of the magnetic dipole in the solving space can be determined by solving the linear equation set The total number of sampling points is P=lenx*leny, wherein lenx is the number of sampling points along the x direction, and leny is the number of sampling points along the y direction.​ 2. The magnetic measurement based multi-target positioning method of claim 1, wherein, the solving algorithm of L1 norm minimization comprises basis pursuit algorithm, interior point method, simplex method, or orthogonal matching pursuit algorithm and primal-dual interior point method.

3. The magnetic measurement based multi-target positioning method according to claim 1, characterized in that, In the data processing step, the solution space is partitioned, and the distance between the magnetic field sensor and the target is required to be greater than 2.5 times the maximum size of the grid.

4. The magnetic measurement based multi-target positioning method of claim 1, wherein, In the setting and partitioning step, the solution space is a cuboid.

5. A multi-target locating system based on magnetic measurements, characterized by It comprises: a. acquisition module, for acquiring magnetic gradient tensor elements above the target and normalized magnetic source strength NSS generated by multiple targets; b. A data processing module for determining normalized magnetic source strength NSS generated by a plurality of targets according to the collected magnetic gradient tensor field, when the distance between the magnetic field sensor and the target is greater than 2.5 times the maximum size of the known target, it is simplified to a point magnetic dipole model, when solving the number n of non-0 magnetic dipoles in the space, the position of the i-th magnetic dipole is , the magnetic moment module is , the total normalized magnetic source strength generated by n magnetic dipoles is , and a coordinate system is established to set up a solving space, vectorize the normalized magnetic source strength collected on the observation plane , and establish a linear equation system between the normalized magnetic source strength and the grid magnetic dipole magnetic moment module. ， wherein is a matrix, is the distance between the i th observation point on the observation plane and the j th magnetic dipole in the solving space, the magnetic moment module distribution of the magnetic dipole in the solving space is determined by solving the linear equation set , and the size and position of the non-0 magnetic moment in the solving space are solved by using the L1 norm minimization method.​ 6. The system of claim 5, wherein, The acquisition module comprises a sensor array for acquiring five magnetic gradient tensor elements 、 、 、 、 and a plurality of normalized magnetic source strengths NSS generated by the targets, the five magnetic gradient tensor elements satisfying the formula wherein is a magnetic gradient tensor element generated by a dipole, is an i component of a magnetic induction intensity, is a j component of a distance vector between an observation point where the magnetic field sensor is located and a target position, the plurality of normalized magnetic source strengths NSS generated by the targets satisfying the formula wherein n is a number of non-zero magnetic dipoles in a solution space, is a position of an i-th magnetic dipole, and a magnetic moment module is .

7. The system of claim 5 or 6, wherein, The system can realize multi-target locating without pre-estimating the number of targets, and further comprises a user interface module for displaying the position and size of non-0 magnetic moment and the number of targets; the system further comprises a calibration module for calibrating the sensor of the acquisition module to improve the measurement accuracy; The system further comprises a data storage module for storing the acquired magnetic gradient tensor field data, the acquired normalized magnetic source strength NSS, the solved position and size of non-0 magnetic moment, and other information.

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