Ground projection method and system for ground-simulated flight aeromagnetic measurement abnormal data of unmanned aerial vehicle

Abstract

The invention discloses a ground projection method and system for aeromagnetic measurement abnormal data of simulated flight of an unmanned aerial vehicle, and belongs to the technical field of processing of aeromagnetic mineral exploration data of the unmanned aerial vehicle, and the method comprises the following steps: obtaining aeromagnetic data of fixed flight height of simulated flight; obtaining frequency spectrum information of a fixed flight height Dirichlet problem solution under the condition of a ground magnetic anomaly initial boundary value; establishing a least square iterative optimization solution of inverse Fourier transform of the aeromagnetic data and the frequency spectrum information; and obtaining ground projection data based on the least square iterative optimization solution. According to the method, the advantage of rapid aeromagnetic data acquisition efficiency of the unmanned aerial vehicle can be brought into play, the aeromagnetic abnormal resolution matched with ground acquisition can be obtained, the method is an efficient and applicable application method technology, and the method technology has great significance in improving the application effect of low-altitude unmanned aerial vehicle aeromagnetic exploration. And the flight height space of aeromagnetic measurement of the unmanned aerial vehicle is expanded remarkably.

Description

Technical Field

[0001] The present invention belongs to the technical field of processing mineral exploration data of unmanned aerial vehicle (UAV) aeromagnetics, and particularly relates to a method and system for ground projection of abnormal data of UAV terrain-following flight aeromagnetic measurement. Background Art

[0002] UAV aeromagnetic measurement has the ability to quickly acquire data relative to the ground. However, aeromagnetic anomalies exponentially decay with the flight altitude, resulting in a significant reduction in the resolution of aeromagnetic anomalies compared to the ground, which is not conducive to the identification of local magnetic source anomalies. Therefore, in order to obtain relatively high-resolution data, most UAV aeromagnetic surveys use low-altitude flight for data collection. However, the improvement of the effect of this measure is very limited, and secondly, the flight risk increases sharply. An effective means to improve the resolution is to directly project and calculate the aeromagnetic anomalies onto the ground, so that high-resolution data similar to ground measurement can be obtained.

[0003] Generally, during the flight of a UAV, various measurement noises and magnetic disturbances are loaded into the aeromagnetic data. Taking this as the first-kind boundary value condition, solving the solution of the Dirichlet lower half-space problem is ill-posed. Therefore, a stable and regular ground projection solution cannot be obtained. The present invention adopts a reverse calculation method, that is, by randomly given ground observation data or aeromagnetic measurement data as the initial boundary value condition, the solution of the Dirichlet upper half-space problem is obtained. Obviously, the analytical calculation under this boundary value condition is a well-posed solution method, and a regular and stable solution on the UAV flight plane can be obtained. Therefore, by comparing and fitting the differences between the calculated data and the measured data on the UAV flight plane, the ground data used as the boundary value condition is iteratively corrected, and finally the ground projection data that meets the correction error can be obtained. Summary of the Invention

[0004] The present invention aims to solve the deficiencies of the prior art and provides the following solutions:

[0005] A method for ground projection of abnormal data of UAV terrain-following flight aeromagnetic measurement, comprising the following steps:

[0006] Obtain aeromagnetic data at a fixed flight altitude of terrain-following flight;

[0007] Obtain the spectral information of the solution of the Dirichlet problem at a fixed flight altitude under the initial boundary value condition of ground magnetic anomalies;

[0008] Establish a least-squares iterative optimization solution of the inverse Fourier transform of the aeromagnetic data and the spectral information;

[0009] Obtain ground projection data based on the least-squares iterative optimization solution.

[0010] Preferably, the method for obtaining the spectral information includes:

[0011] ,

[0012] Among them, represents the spectral information of the UAV flight surface, represents the initial boundary value condition Fourier transform of, u and v represent spatial frequencies, and z represents the solution height in the upper half space.

[0013] Preferably, the method for establishing the least squares iterative optimization solution includes:

[0014] Perform inverse Fourier transform on the spectral information to calculate the magnetic anomaly data of the flight surface based on the initial boundary value condition:

[0015] ,

[0016] Among them, represents the magnetic anomaly data, and F -1 represents the inverse Fourier transform;

[0017] Based on the difference between the magnetic anomaly data and the aeromagnetic data correct the initial boundary value condition to obtain the least squares iterative optimization solution:

[0018] ,

[0019] Among them, represents the least squares iterative optimization solution, and k represents the step size.

[0020] Preferably, the method for obtaining the ground projection data includes:

[0021] Repeatedly calculate the least squares iterative optimization solution to obtain the least squares iterative optimization solution under the nth ground magnetic anomaly boundary condition :

[0022] ,

[0023] Among them, represents the magnetic anomaly data of the nth ground magnetic anomaly boundary condition, represents the Fourier transform of the nth calculated ground magnetic anomaly boundary condition, and at this time there is:

[0024] ,

[0025] Among them, represents the least squares iterative optimization solution solved for the nth time, represents the nth calculated ground magnetic anomaly boundary condition;

[0026] When When there is, then there are:

[0027] ,

[0028] ,

[0029] That is, the boundary value condition of the ground magnetic anomaly for the nth calculation is the aeromagnetic data The ground projection data on the ground, where ε represents a constant approaching zero.

[0030] The present invention also provides a ground projection system for abnormal data of unmanned aerial vehicle (UAV) terrain-following flight aeromagnetic measurement. The system applies the method described in any one of the above, and includes: an aeromagnetic data acquisition module, a spectral information acquisition module, an optimal solution calculation module, and a projection data calculation module;

[0031] The aeromagnetic data acquisition module is used to acquire aeromagnetic data at a fixed flight altitude of terrain-following flight;

[0032] The spectral information acquisition module is used to acquire spectral information of the solution of the Dirichlet problem at a fixed flight altitude under the initial boundary value condition of the ground magnetic anomaly;

[0033] The optimal solution calculation module is used to establish a least squares iterative optimal solution of the inverse Fourier transform of the aeromagnetic data and the spectral information;

[0034] The projection data calculation module obtains ground projection data based on the least squares iterative optimal solution.

[0035] Preferably, the working process of the spectral information acquisition module includes:

[0036] ,

[0037] Among them, represents the spectral information of the UAV flight surface, represents the initial boundary value condition The Fourier transform of, u and v represent spatial frequencies, and z represents the solution height in the upper half space.

[0038] Preferably, the working process of the optimal solution calculation module includes:

[0039] Perform an inverse Fourier transform on the spectral information, and calculate the magnetic anomaly data of the flight surface based on the initial boundary value condition:

[0040] ,

[0041] Among them, represents the magnetic anomaly data, and F -1 represents the inverse Fourier transform;

[0042] Based on the magnetic anomaly data and the airborne magnetic data to correct the initial boundary value condition, and obtain the least squares iterative optimization solution:

[0043] ,

[0044] wherein, represents the least squares iterative optimization solution, and k represents the step size.

[0045] Preferably, the working process of the projection data calculation module includes:

[0046] Repeatedly calculate the least squares iterative optimization solution to obtain the least squares iterative optimization solution under the nth ground magnetic anomaly boundary value condition as follows:

[0047] ,

[0048] wherein, represents the magnetic anomaly data of the nth ground magnetic anomaly boundary value condition, represents the Fourier transform of the nth calculated ground magnetic anomaly boundary value condition, and at this time there is:

[0049] ,

[0050] wherein, represents the least squares iterative optimization solution solved for the nth time, represents the nth calculated ground magnetic anomaly boundary value condition;

[0051] When , then there is:

[0052] ,

[0053] ,

[0054] that is, the nth calculated ground magnetic anomaly boundary value condition is the ground projection data of the airborne magnetic data on the ground, wherein, ε represents a constant approaching zero.

[0055] Compared with the prior art, the beneficial effects of the present invention are:

[0056] The present invention can not only give full play to the advantages of the high data acquisition efficiency of unmanned aerial vehicle (UAV) airborne magnetic survey, but also obtain the airborne magnetic anomaly resolution matching that of ground acquisition. It is an efficient and applicable application method technology, and this method technology has a significant effect on improving the application effect of low-altitude UAV airborne magnetic exploration and expanding the flight altitude space of UAV airborne magnetic survey. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0058] Figure 1 It is a schematic flowchart of the method according to an embodiment of the present invention;

[0059] Figure 2 It is a simplified diagram of the undulating ground and the ground-following flight surface of the unmanned aerial vehicle according to an embodiment of the present invention;

[0060] Figure 3 It is a schematic diagram of the spatial position of the magnetic source model according to an embodiment of the present invention;

[0061] Figure 4 It is the ground-following flight surface S according to an embodiment of the present invention h Measured magnetic anomaly That is, the ground S 0 Data ;

[0062] Figure 5 It is the airborne magnetic anomaly data of the ground-following flight surface S obtained through calculation according to an embodiment of the present invention h ; ;

[0063] Figure 6 It is the surface S according to an embodiment of the present invention h Measured airborne magnetic anomaly And calculated airborne magnetic anomaly The fitting effect diagram of the difference P between the two;

[0064] Figure 7 It is a schematic diagram of the data 0 Of the ground S obtained after the second iterative correction according to an embodiment of the present invention ;

[0065] Figure 8 It is the measured airborne magnetic anomaly data of the ground-following flight surface S of the unmanned aerial vehicle after n iterative corrections according to an embodiment of the present invention h ; On the ground S 0 Projection data Schematic diagram. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0066] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0067] To make the above objects, features, and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0068] Embodiment 1:

[0069] In this embodiment, as Figure 1 shown, a method for ground projection of abnormal data in drone terrain-following flight aeromagnetic measurement includes the following steps:

[0070] S1. Obtain the aeromagnetic data at a fixed flight altitude of terrain-following flight.

[0071] In this embodiment, the aeromagnetic data at a fixed altitude is measured by a drone in terrain-following flight as , and a random ground data is given. The random data given in this embodiment is the actually measured aeromagnetic data , and let it be used as the initial boundary condition of the first kind. Here, it is defined as .

[0072] S2. Obtain the spectral information of the solution of the Dirichlet problem at a fixed flight altitude under the initial boundary condition of ground magnetic anomaly.

[0073] Establish the solution equation of the Dirichlet upper half-space problem based on the initial boundary condition of the first kind , that is:

[0074] ,

[0075] wherein, represents the integration variable on the x-axis, η represents the integration variable on the y-axis; the solution process is realized in the frequency domain, that is, the fast Fourier transform is performed on each term of the above equation to obtain the spectral information of the solution of the drone flight surface:

[0076] ,

[0077] wherein, represents the spectral information of the drone flight surface, FT represents the Fourier transform, represents the Fourier transform of the initial boundary condition , u and v represent the spatial frequencies, representing the wave numbers of x and y respectively, and z represents the solution height in the upper half-space.

[0078] S3. Establish the least - squares iterative optimization solution of the inverse Fourier transform of aeromagnetic data and spectral information.

[0079] The method for establishing the least - squares iterative optimization solution includes: performing an inverse Fourier transform on the spectral information and calculating the magnetic anomaly data of the flight surface based on the initial boundary conditions:

[0080] ,

[0081] where, represents the magnetic anomaly data, and F -1 represents the inverse Fourier transform; based on the difference between the magnetic anomaly data and the aeromagnetic data , the initial boundary conditions are corrected to obtain the least - squares iterative optimization solution:

[0082] ,

[0083] where, represents the least - squares iterative optimization solution, k represents the step size, which can be adaptively corrected or a fixed step size can be taken. In this embodiment, the fixed step size is taken as 1.

[0084] S4. Obtain the ground projection data based on the least - squares iterative optimization solution.

[0085] The method for obtaining the ground projection data includes:

[0086] Taking the ground data after the first correction as the boundary conditions for the next calculation, repeating the calculations of S2 and S3, solving the Dirichlet upper - half - space problem in the frequency domain, and then correcting according to the calculated difference to obtain the ground data after the second correction ; then taking the ground data again as the first - type boundary conditions, calculating cyclically in turn, repeating the calculation of the least - squares iterative optimization solution, and obtaining the least - squares iterative optimization solution under the nth ground magnetic anomaly boundary conditions :

[0087] ,

[0088] where, represents the magnetic anomaly data of the nth ground magnetic anomaly boundary conditions, represents the Fourier transform of the nth calculated ground magnetic anomaly boundary conditions, and at this time there is:

[0089] ,

[0090] where, Denote the least - squares iterative optimization solution for the n - th solution, Denote the boundary value condition of the ground magnetic anomaly for the n - th calculation;

[0091] When Then there is:

[0092] ,

[0093] ,

[0094] That is, the boundary value condition of the ground magnetic anomaly for the n - th calculation is the ground projection data of the aeromagnetic data on the ground, where ε represents a constant approaching zero.

[0095] Embodiment 2:

[0096] In this embodiment, a method for ground projection of abnormal data in aeromagnetic measurement of an unmanned aerial vehicle flying following the ground includes the following steps:

[0097] S1. Obtain the aeromagnetic data at a fixed flight altitude of flying following the ground.

[0098] In this embodiment, as Figure 2 shown, assume that the unmanned aerial vehicle flight surface S z and the ground S 0 are a set of parallel surfaces, where the flight altitude of the unmanned aerial vehicle is the fixed altitude z = h for flying following the ground, and the altitude of the ground S 0 is defined as z = 0; design a magnetic source model as Figure 3 shown, and the magnetic anomaly measured on the flight surface S h for flying following the ground is ; regard as the data of the ground S 0 , that is , as the initial boundary condition of the first kind for the Direchlet upper - half - space problem, as Figure 4 shown;

[0099] S2. Obtain the spectral information of the solution of the Dirichlet problem at a fixed flight altitude under the initial boundary condition of the ground magnetic anomaly.

[0100] Establish the solution equation of the Direchlet upper - half - space problem based on the first - kind boundary condition , that is:

[0101] ,

[0102] where, Let \(x\) represent the integration variable on the \(x\)-axis, and \(\eta\) represent the integration variable on the \(y\)-axis. When the altitude of the unmanned aerial vehicle (UAV) flying following the terrain is a fixed altitude \(z = h\), its solution process is realized in the frequency domain, that is, a fast Fourier transform is performed on each term of the above equation to obtain the solution \(S\) of the UAV flight surface h of the spectral information :

[0103] ,

[0104] wherein, represents the spectral information of the UAV flight surface, \(FT\) represents the Fourier transform, represents the Fourier transform of the initial boundary value condition , \(u\) and \(v\) represent the spatial frequencies, representing the wave numbers of \(x\) and \(y\) respectively, and \(h\) represents the solution height in the upper half space.

[0105] S3. Establish a least-squares iterative optimization solution for the inverse Fourier transform of the aeromagnetic data and the spectral information.

[0106] The method for establishing the least-squares iterative optimization solution includes: performing an inverse Fourier transform on the spectral information, calculating the magnetic anomaly data of the flight surface based on the initial boundary value condition, as Figure 5 shown:

[0107] ,

[0108] wherein, represents the magnetic anomaly data, \(F\) -1 represents the inverse Fourier transform; solve for the flight surface \(S\) h the measured aeromagnetic anomaly and the aeromagnetic anomaly calculated in the above steps the difference between the two , and the fitting effect of the two is as Figure 6 shown; according to the above difference \(P\), obtain the ground \(S\) after the first correction 0 The first type of boundary value data:

[0109] ,

[0110] wherein, represents the least-squares iterative optimization solution, \(k\) represents the step size, which can be adaptively corrected or a fixed step size can be taken. In this embodiment, the fixed step size is taken as 1.

[0111] S4. Obtain the ground projection data based on the least-squares iterative optimization solution.

[0112] The method for obtaining the ground projection data includes:

[0113] the ground data after the first correction As the boundary value condition for the next calculation, repeat the calculations of S2 and S3, solve the Direchlet upper half-space problem in the frequency domain, and then correct according to the difference of the calculated to obtain the ground S after the second correction 0 ground data , such as Figure 7 shown; then use the ground data again as the first-kind boundary value condition, calculate iteratively in turn, repeat the calculation of the least-squares iterative optimization solution, and obtain the least-squares iterative optimization solution under the nth ground magnetic anomaly boundary value condition :

[0114] ,

[0115] wherein, represents the flight surface S after the nth correction h magnetic anomaly data of the ground magnetic anomaly boundary value condition, represents the Fourier transform of the ground magnetic anomaly boundary value condition calculated for the nth time, and at this time there is:

[0116] ,

[0117] wherein, represents the least-squares iterative optimization solution solved for the nth time, represents the ground magnetic anomaly boundary value condition calculated for the nth time;

[0118] When , then there is:

[0119] ,

[0120] wherein, ε represents a constant approaching zero; the number of correction iterations n is generally taken as 40 - 50 times, and at this time the difference between the calculated data and the measured data meets the error requirements designed in this example; output the ground data after the nth correction:

[0121] ,

[0122] that is, obtain the projection data h of the measured airborne magnetic anomaly data on the ground S_0 , such as Figure 8 shown.

[0123] Figures 2 - 8Among them, nT represents the unit of aeromagnetic anomaly, X represents the east-west direction of the geographical location, Y represents the north-south direction of the geographical location, Z represents the distance of the unmanned aerial vehicle flying following the terrain, h represents the solving height in the upper half space, and A / M represents the unit of magnetic field strength.

[0124] Embodiment 3:

[0125] In this embodiment, a ground projection system for abnormal data of unmanned aerial vehicle flying following the terrain for aeromagnetic measurement includes: an aeromagnetic data acquisition module, a spectrum information acquisition module, an optimized solution calculation module, and a projection data calculation module.

[0126] The aeromagnetic data acquisition module is used to acquire aeromagnetic data at a fixed flying height of flying following the terrain.

[0127] The spectrum information acquisition module is used to acquire the spectrum information of the solution of the Dirichlet problem at a fixed flying height under the initial boundary value conditions of the ground magnetic anomaly.

[0128] The working process of the spectrum information acquisition module includes:

[0129] ,

[0130] Among them, represents the spectrum information of the unmanned aerial vehicle flight surface, represents the initial boundary value condition of the Fourier transform, u and v represent spatial frequencies, and z represents the solving height in the upper half space.

[0131] The optimized solution calculation module is used to establish a least-squares iterative optimized solution of the inverse Fourier transform of the aeromagnetic data and the spectrum information.

[0132] The working process of the optimized solution calculation module includes: performing an inverse Fourier transform on the spectrum information and calculating the magnetic anomaly data of the flight surface based on the initial boundary value conditions:

[0133] ,

[0134] Among them, represents the magnetic anomaly data, F -1 represents the inverse Fourier transform; based on the difference between the magnetic anomaly data and the aeromagnetic data to correct the initial boundary value condition, and obtain the least-squares iterative optimized solution:

[0135] ,

[0136] Among them, represents the least-squares iterative optimized solution, and k represents the step size.

[0137] The projection data calculation module obtains the ground projection data based on the least squares iterative optimization solution.

[0138] The working process of the projection data calculation module includes: repeatedly calculating the least squares iterative optimization solution to obtain the least squares iterative optimization solution under the magnetic anomaly boundary condition of the ground for the nth time as follows:

[0139] ,

[0140] wherein, represents the magnetic anomaly data of the magnetic anomaly boundary condition of the ground for the nth time, represents the Fourier transform of the magnetic anomaly boundary condition of the ground calculated for the nth time. At this time, there is:

[0141] ,

[0142] wherein, represents the least squares iterative optimization solution solved for the nth time, represents the magnetic anomaly boundary condition of the ground calculated for the nth time; when is satisfied, then there is:

[0143] ,

[0144] ,

[0145] that is, the magnetic anomaly boundary condition of the ground calculated for the nth time is the ground projection data of the aeromagnetic data on the ground, where ε represents a constant approaching zero.

[0146] The embodiments described above are only descriptions of the preferred embodiments of the present invention, and do not limit the scope of the present invention. Without departing from the design spirit of the present invention, various deformations and improvements made by those of ordinary skill in the art to the technical solutions of the present invention should fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for ground projection of abnormal data of aeromagnetic measurement by unmanned aerial vehicle ground imitation flight, characterized in that: The following steps are involved: Obtain aeromagnetic data at a fixed flight altitude for terrain-simulating flight; Obtain the spectrum information of the solution of the Dirichlet problem with fixed flight altitude under the initial boundary conditions of ground magnetic anomaly; Establishing a least squares iterative optimization solution of the inverse Fourier transform of the aeromagnetic data and the frequency spectrum information; The ground projection data is obtained based on the least squares iterative optimization solution.

2. According to claim 1, a method for ground projection of abnormal data of aeromagnetic measurement by unmanned aerial vehicle terrain imitation flight, characterized in that: The method for obtaining the spectrum information includes: ， in, Represents the frequency spectrum information of the UAV flight surface, represents the initial boundary condition Fourier transform, u and v represent the spatial frequencies, and z represents the height of the upper half space solution.

3. According to claim 2, a method for ground projection of abnormal data of aeromagnetic measurement by unmanned aerial vehicle terrain simulation flight, characterized in that: The method for establishing the least squares iterative optimization solution includes: Performing an inverse Fourier transform on the frequency spectrum information to calculate the magnetic anomaly data of the flight surface based on the initial boundary value conditions: ， in, Represents magnetic anomaly data, F -1 represents inverse Fourier transform; Based on the magnetic anomaly data and the aeromagnetic data The initial boundary condition is corrected by the difference of , and the least squares iterative optimization solution is obtained: ， in, represents the least squares iterative optimization solution, and k represents the step size.

4. According to claim 3, a method for ground projection of abnormal data of aeromagnetic measurement by unmanned aerial vehicle terrain simulation flight, characterized in that: Methods for obtaining ground projection data include: Repeat the least squares iterative optimization solution to obtain the nth ground magnetic anomaly boundary condition. The least squares iterative optimization solution under : ， in, The magnetic anomaly data representing the boundary conditions of the nth ground magnetic anomaly, The Fourier transform of the boundary condition of the ground magnetic anomaly calculated for the nth time is: ， in, represents the least squares iterative optimization solution of the nth solution, represents the boundary condition of the ground magnetic anomaly calculated for the nth time; when When , we have: ， ， That is, the calculated nth ground magnetic anomaly boundary condition is the aeromagnetic data The ground projection data on the ground, wherein ε represents a constant approaching zero.

5. A ground projection system for abnormal data of aeromagnetic measurement by unmanned aerial vehicle terrain imitation flight, the system applying the method according to any one of claims 1 to 4, characterized in that: include: Aeromagnetic data acquisition module, spectrum information acquisition module, optimization solution calculation module and projection data calculation module; The aeromagnetic data acquisition module is used to acquire aeromagnetic data of a fixed flight altitude for terrain simulation flight; The spectrum information acquisition module is used to acquire spectrum information of the solution of the Dirichlet problem with a fixed flight altitude under the initial boundary value conditions of the ground magnetic anomaly; The optimization solution calculation module is used to establish a least squares iterative optimization solution of the inverse Fourier transform of the aeromagnetic data and the spectrum information; The projection data calculation module obtains ground projection data based on the least squares iterative optimization solution.

6. According to claim 5, a ground projection system for abnormal data of aeromagnetic measurement by unmanned aerial vehicle terrain imitation flight, characterized in that: The workflow of the spectrum information acquisition module includes: ， in, Represents the frequency spectrum information of the UAV flight surface, represents the initial boundary condition Fourier transform, u and v represent the spatial frequencies, and z represents the height of the upper half space solution.

7. A ground projection system for abnormal data of aeromagnetic measurement by unmanned aerial vehicle terrain imitation flight according to claim 6, characterized in that: The workflow of the optimization solution calculation module includes: Performing an inverse Fourier transform on the frequency spectrum information to calculate the magnetic anomaly data of the flight surface based on the initial boundary value conditions: ， in, Represents magnetic anomaly data, F -1 represents inverse Fourier transform; Based on the magnetic anomaly data and the aeromagnetic data The initial boundary condition is corrected by the difference of , and the least squares iterative optimization solution is obtained: ， in, represents the least squares iterative optimization solution, and k represents the step size.

8. The ground projection system for abnormal data of aeromagnetic measurement by unmanned aerial vehicle terrain imitation flight according to claim 7, characterized in that: The workflow of the projection data calculation module includes: Repeat the least squares iterative optimization solution to obtain the nth ground magnetic anomaly boundary condition. The least squares iterative optimization solution under : ， in, The magnetic anomaly data representing the boundary conditions of the nth ground magnetic anomaly, The Fourier transform of the boundary condition of the ground magnetic anomaly calculated for the nth time is: ， in, represents the least squares iterative optimization solution of the nth solution, represents the boundary condition of the ground magnetic anomaly calculated for the nth time; when When , we have: ， ， That is, the calculated nth ground magnetic anomaly boundary condition is the aeromagnetic data The ground projection data on the ground, wherein ε represents a constant approaching zero.

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