A ground projection method and system for abnormal data of aeromagnetic measurement by unmanned aerial vehicle (UAV) using ground-simulating flight

Abstract

The present invention discloses a method and system for ground projection of anomaly data from aeromagnetic measurements taken by unmanned aerial vehicle (UAV) during terrestrial flight. This method belongs to the technical field of processing UAV aeromagnetic mineral exploration data. The method comprises the following steps: obtaining aeromagnetic data at a fixed flight altitude during terrestrial flight; obtaining spectral information of a solution to a Dirichlet problem at a fixed flight altitude under initial boundary conditions of ground magnetic anomalies; establishing a least squares iterative optimization solution for the inverse Fourier transform of the aeromagnetic data and the spectral information; and obtaining ground projection data based on the least squares iterative optimization solution. The present invention leverages the advantages of UAV aeromagnetic's rapid data acquisition efficiency while achieving aeromagnetic anomaly resolution that matches ground acquisition. This method and technology are highly efficient and applicable, significantly contributing to improving the application of low-altitude UAV aeromagnetic exploration and expanding the flight altitude space for UAV aeromagnetic measurements.

Description

Technical Field

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

[0002] While drone-based aeromagnetic surveys offer the ability to acquire data more quickly than ground-based surveys, aeromagnetic anomalies decay exponentially with altitude, significantly reducing the resolution of aeromagnetic data compared to ground-based surveys. This hinders the identification of localized magnetic anomalies. Therefore, to obtain relatively high-resolution data, drone-based aeromagnetic surveys are often performed at low altitudes. However, this approach offers limited improvement and significantly increases the risk of flight. An effective approach to improving resolution is to project aeromagnetic anomalies directly onto the ground, yielding data at the same high resolution as ground-based surveys.

[0003] Typically, during drone flight, aeromagnetics will load various measurement noises and magnetic disturbances. Using these as first-order boundary conditions, the solution to the Dirichlet lower half-space problem is ill-posed, and therefore, a stable and regular ground projection solution cannot be obtained. The present invention adopts a calculation method that is the opposite of this, that is, using randomly given ground observation data or aeromagnetic measurement data as initial boundary conditions to solve the Dirichlet upper half-space problem. Obviously, the analytical calculation under this boundary condition is a well-posed solution method that can obtain a regular and stable solution on the drone flight surface. Therefore, by comparing the difference between the calculated data and the measured data of the drone flight surface, the ground data used as the boundary conditions are 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 from aeromagnetic measurement by a UAV using a ground-simulating flight method comprises the following steps:

[0006] Acquire aeromagnetic data at a fixed flight altitude for terrain simulation flight;

[0007] Obtain the spectrum information of the solution of the Dirichlet problem with fixed flight altitude under the initial boundary conditions of ground magnetic anomaly;

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

[0009] Ground projection data is obtained based on the least squares iterative optimization solution.

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

[0011] ,

[0012] in, Represents the spectrum information of the UAV flight surface, represents the initial boundary conditions Fourier transform, u and v represent spatial frequencies, and z represents the height of the upper half space solution.

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

[0014] Performing an inverse Fourier transform on the frequency spectrum information to calculate magnetic anomaly data of the flight surface based on the initial boundary conditions:

[0015] ,

[0016] in, Represents magnetic anomaly data, F -1 represents the inverse Fourier transform;

[0017] Based on the magnetic anomaly data and the aeromagnetic data The initial boundary conditions are modified by the difference of , and the least squares iterative optimization solution is obtained:

[0018] ,

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

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

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

[0022] ,

[0023] 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:

[0024] ,

[0025] in, represents the least squares iterative optimization solution of the nth solution, Indicates the boundary condition of the ground magnetic anomaly calculated for the nth time;

[0026] when When , there are:

[0027] ,

[0028] ,

[0029] That is, the calculated n-th ground magnetic anomaly boundary condition is the aeromagnetic data The ground projection data on the ground, wherein ε represents a constant approaching zero.

[0030] The present invention also provides a ground projection system for abnormal data of aeromagnetic measurement by a UAV during terrestrial flight, wherein the system applies any of the above-mentioned methods and comprises: an aeromagnetic data acquisition module, a spectrum information acquisition module, an optimization 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 for terrain simulation flight;

[0032] The spectrum information acquisition module is used to obtain spectrum information of the solution of the Dirichlet problem with fixed flight altitude under the initial boundary value conditions of ground magnetic anomaly;

[0033] 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;

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

[0035] Preferably, the workflow of the spectrum information acquisition module includes:

[0036] ,

[0037] in, Represents the spectrum information of the UAV flight surface, represents the initial boundary conditions Fourier transform, u and v represent spatial frequencies, and z represents the height of the upper half space solution.

[0038] Preferably, the workflow of the optimization solution calculation module includes:

[0039] Performing an inverse Fourier transform on the frequency spectrum information to calculate magnetic anomaly data of the flight surface based on the initial boundary conditions:

[0040] ,

[0041] in, Represents magnetic anomaly data, F -1 represents the inverse Fourier transform;

[0042] Based on the magnetic anomaly data and the aeromagnetic data The initial boundary conditions are modified by the difference of , and the least squares iterative optimization solution is obtained:

[0043] ,

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

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

[0046] Repeat the least squares iterative optimization solution to obtain the nth ground magnetic anomaly boundary condition The least squares iterative optimization solution under :

[0047] ,

[0048] 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:

[0049] ,

[0050] in, represents the least squares iterative optimization solution of the nth solution, Indicates the boundary condition of the ground magnetic anomaly calculated for the nth time;

[0051] when When , there are:

[0052] ,

[0053] ,

[0054] That is, the calculated n-th ground magnetic anomaly boundary condition is the aeromagnetic data The ground projection data on the ground, wherein ε represents a constant approaching zero.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] The present invention can not only give full play to the advantages of UAV aeromagnetic's rapid data acquisition efficiency, but also obtain aeromagnetic anomaly resolution that matches ground acquisition. It is an efficient and applicable application method and technology. This method and technology has a significant effect on improving the application effect of low-altitude UAV aeromagnetic exploration and expanding the flight altitude space of UAV aeromagnetic measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0058] Figure 1 Schematic diagram of a method flow in an embodiment of the present invention;

[0059] Figure 2 A simplified diagram of an undulating ground surface and a UAV's terrain-imitating flight surface according to an embodiment of the present invention;

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

[0061] Figure 4 The ground-simulating flight surface S in the embodiment of the present invention h Measured magnetic anomalies That is, the ground S0 data ;

[0062] Figure 5 The UAV terrain-simulating flight surface S is obtained by calculation according to the embodiment of the present invention. h Aeromagnetic anomaly data ;

[0063] Figure 6 The curved surface S of the embodiment of the present invention h Measured aeromagnetic anomalies and calculating aeromagnetic anomalies The fitting effect diagram of the difference P between the two;

[0064] Figure 7 The data of ground S0 obtained after the second iteration correction in the embodiment of the present invention is Schematic diagram;

[0065] Figure 8 The UAV terrain-simulating flight surface S after n iterations of correction in the embodiment of the present invention is h Measured aeromagnetic anomaly data Projection data on the ground S0 Schematic diagram. DETAILED DESCRIPTION

[0066] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0067] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0068] Example 1:

[0069] In this embodiment, if Figure 1 As shown, a ground projection method for abnormal data of aeromagnetic measurement by a UAV simulated ground flight includes the following steps:

[0070] S1. Acquire aeromagnetic data at a fixed altitude for terrain simulation flight.

[0071] In this embodiment, the aeromagnetic data at a fixed height measured by the drone is , given a random ground data, the random data given in this embodiment is the aeromagnetic measured data , let it be the first kind of boundary value initial condition, here we define .

[0072] S2. Obtain the spectrum information of the solution of the Dirichlet problem with fixed flight altitude under the initial boundary conditions of ground magnetic anomaly.

[0073] Establish a boundary condition based on the first kind The solution equation of Direchlet's upper half-space problem under , namely:

[0074] ,

[0075] in, represents the integral variable on the x-axis, and η represents the integral 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 spectrum information of the UAV flight surface solution:

[0076] ,

[0077] in, Represents the frequency spectrum information of the UAV flight surface, FT represents Fourier transform, represents the initial boundary conditions The Fourier transform of , u and v represent the spatial frequency, respectively represent the wave number of x and y, and z represents the height of the upper half space solution.

[0078] S3. Establish a least squares iterative optimization solution for 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 spectrum information and calculating the magnetic anomaly data of the flight surface based on the initial boundary value conditions:

[0080] ,

[0081] in, Represents magnetic anomaly data, F -1 Represents inverse Fourier transform; based on magnetic anomaly data and aeromagnetic data The initial boundary conditions are modified by the difference of , and the least squares iterative optimization solution is obtained:

[0082] ,

[0083] in, represents the least squares iterative optimization solution, k represents the step size, which can be adaptively modified or fixed. In this embodiment, the fixed step size is 1.

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

[0085] Methods for obtaining ground projection data include:

[0086] The ground data after the first correction As the boundary condition for the next calculation, repeat the S2 and S3 calculations, solve the Dirichlet upper half-space problem in the frequency domain, and then calculate the The difference correction is used to obtain the ground data after the second correction. ; Then the ground data Again as the first type of boundary condition, the calculation is repeated in sequence, and the least squares iterative optimization solution is repeatedly calculated to obtain the nth ground magnetic anomaly boundary condition The least squares iterative optimization solution under :

[0087] ,

[0088] 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:

[0089] ,

[0090] in, represents the least squares iterative optimization solution of the nth solution, Indicates the boundary condition of the ground magnetic anomaly calculated for the nth time;

[0091] when When , there are:

[0092] ,

[0093] ,

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

[0095] Example 2:

[0096] In this embodiment, a method for ground projection of abnormal data from aeromagnetic measurement by a drone during ground-simulating flight includes the following steps:

[0097] S1. Acquire aeromagnetic data at a fixed altitude for terrain simulation flight.

[0098] In this embodiment, if Figure 2 As shown, assuming that the UAV flight surface S z and the ground S0 are a set of parallel surfaces, where the UAV's flight height is the fixed height z=h of the simulated ground, and the height of the ground S0 is defined as z=0; the design is as follows Figure 3 The magnetic source model shown in the figure is on the simulated flight surface S h The measured magnetic anomaly is ;Will Considered as ground S0 data, that is , as the first kind of boundary value initial condition for Dirichlet upper half-space problem, such as Figure 4 As shown;

[0099] S2. Obtain the spectrum information of the solution of the Dirichlet problem with fixed flight altitude under the initial boundary conditions of ground magnetic anomaly.

[0100] Establish a boundary condition based on the first kind The solution equation of Direchlet's upper half-space problem under , namely:

[0101] ,

[0102] in, represents the integral variable on the x-axis, and η represents the integral variable on the y-axis. When the UAV’s terrain-simulating flight altitude is a fixed altitude z=h, the solution process is realized in the frequency domain, that is, the above equations are fast Fourier transformed to obtain the UAV flight surface solution Sh Spectrum information :

[0103] ,

[0104] in, Represents the frequency spectrum information of the UAV flight surface, FT represents Fourier transform, represents the initial boundary conditions Fourier transform, u and v represent the spatial frequency, respectively represent the wave number of x and y, and h represents the height of the upper half space solution.

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

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

[0107] ,

[0108] in, Represents magnetic anomaly data, F -1 represents the inverse Fourier transform; solve the flight surface S h Measured aeromagnetic anomalies and the aeromagnetic anomaly calculated in the above steps The difference between the two The fitting effect of the two is as follows Figure 6 As shown; Based on the above difference P, the first-class boundary value data of the ground S0 after the first correction is obtained:

[0109] ,

[0110] in, represents the least squares iterative optimization solution, k represents the step size, which can be adaptively modified or fixed. In this embodiment, the fixed step size is 1.

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

[0112] Methods for obtaining ground projection data include:

[0113] The ground data after the first correction As the boundary condition for the next calculation, repeat the S2 and S3 calculations, solve the Dirichlet upper half-space problem in the frequency domain, and then calculate the The difference correction is used to obtain the ground data of S0 after the second correction. ,like Figure 7 As shown; then the ground data Again as the first type of boundary condition, the calculation is repeated in sequence, and the least squares iterative optimization solution is repeatedly calculated to obtain the nth ground magnetic anomaly boundary condition The least squares iterative optimization solution under :

[0114] ,

[0115] in, Represents the flight surface S after the nth correction h Magnetic anomaly data of ground magnetic anomaly boundary conditions, The Fourier transform of the boundary condition of the ground magnetic anomaly calculated for the nth time is:

[0116] ,

[0117] in, represents the least squares iterative optimization solution of the nth solution, Indicates the boundary condition of the ground magnetic anomaly calculated for the nth time;

[0118] when When , there are:

[0119] ,

[0120] Among them, ε represents a constant close to zero; the number of correction iterations n is generally 40 to 50 times, at which time the calculated data and measured data The difference meets the error requirements of this example design; output the ground data after the nth correction :

[0121] ,

[0122] That is, the UAV ground-simulating flight surface S is obtained h Measured aeromagnetic anomaly data Projection data on the ground S_0 ,like Figure 8 shown.

[0123] Figure 2-Figure 8 In the figure, nT represents the unit of aeromagnetic anomaly, X represents the east-west direction of the geographic location, Y represents the north-south direction of the geographic location, Z represents the distance of the UAV's terrain simulation flight, h represents the upper half-space solution height, and A / M represents the unit of magnetic field intensity.

[0124] Example 3:

[0125] In this embodiment, a ground projection system for abnormal data of aeromagnetic measurement by a UAV during terrain simulation flight includes: an aeromagnetic data acquisition module, a spectrum information acquisition module, an optimization solution calculation module, and a projection data calculation module.

[0126] The aeromagnetic data acquisition module is used to obtain aeromagnetic data at a fixed flight altitude for terrain simulation flight.

[0127] The spectrum information acquisition module is used to obtain the spectrum information of the solution of the Dirichlet problem with fixed flight altitude under the initial boundary conditions of ground magnetic anomaly.

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

[0129] ,

[0130] in, Represents the spectrum information of the UAV flight surface, represents the initial boundary conditions Fourier transform, u and v represent spatial frequencies, and z represents the height of the upper half space solution.

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

[0132] The workflow of the optimization solution calculation module includes: performing 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] in, Represents magnetic anomaly data, F -1 Represents inverse Fourier transform; based on magnetic anomaly data and aeromagnetic data The initial boundary conditions are modified by the difference of , and the least squares iterative optimization solution is obtained:

[0135] ,

[0136] in, represents the least squares iterative optimization 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 workflow of the projection data calculation module includes: repeatedly calculating the least squares iterative optimization solution to obtain the nth ground magnetic anomaly boundary condition The least squares iterative optimization solution under :

[0139] ,

[0140] 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:

[0141] ,

[0142] in, represents the least squares iterative optimization solution of the nth solution, Indicates the boundary condition of the ground magnetic anomaly calculated for the nth time; when When , there are:

[0143] ,

[0144] ,

[0145] That is, the boundary condition of the calculated n-th ground magnetic anomaly is the aeromagnetic data Ground projection data on the ground, where ε represents a constant approaching zero.

[0146] The embodiments described above are merely descriptions of preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by persons skilled in the art should fall within the scope of protection defined by the claims of the present invention.

Claims

1. A method for ground projection of abnormal data from aeromagnetic measurement by a UAV using a ground-simulating flight, characterized in that: The following steps are involved: Acquire aeromagnetic data at a fixed flight altitude for terrain simulation 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 spectral information; Obtaining ground projection data based on the least squares iterative optimization solution; The method for obtaining the spectrum information includes: ， in, Represents the spectrum information of the UAV flight surface, represents the initial boundary conditions Fourier transform, u and v represent spatial frequencies, and z represents the height of the upper half space solution; The method for establishing the least squares iterative optimization solution includes: Performing an inverse Fourier transform on the frequency spectrum information to calculate magnetic anomaly data of the flight surface based on the initial boundary conditions: ， in, Represents magnetic anomaly data, F -1 represents the inverse Fourier transform; Based on the magnetic anomaly data and the aeromagnetic data The initial boundary conditions are modified by the difference of , and the least squares iterative optimization solution is obtained: ， in, represents the least squares iterative optimization solution, k represents the step size; 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, Indicates the boundary condition of the ground magnetic anomaly calculated for the nth time; when When , there are: ， ， That is, the calculated n-th ground magnetic anomaly boundary condition is the aeromagnetic data The ground projection data on the ground, wherein ε represents a constant approaching zero.

2. A ground projection system for aeromagnetic measurement of abnormal data by a drone using a ground-simulating flight, wherein the system applies the method of claim 1, 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 at a fixed flight altitude for terrain simulation flight; The spectrum information acquisition module is used to obtain spectrum information of the solution of the Dirichlet problem with fixed flight altitude under the initial boundary value conditions of 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; The workflow of the spectrum information acquisition module includes: ， in, Represents the spectrum information of the UAV flight surface, represents the initial boundary conditions Fourier transform, u and v represent spatial frequencies, and z represents the height of the upper half space solution; The workflow of the optimization solution calculation module includes: Performing an inverse Fourier transform on the frequency spectrum information to calculate magnetic anomaly data of the flight surface based on the initial boundary conditions: ， in, Represents magnetic anomaly data, F -1 represents the inverse Fourier transform; Based on the magnetic anomaly data and the aeromagnetic data The initial boundary conditions are modified by the difference of , and the least squares iterative optimization solution is obtained: ， in, represents the least squares iterative optimization solution, k represents the step size; 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, Indicates the boundary condition of the ground magnetic anomaly calculated for the nth time; when When , there are: ， ， That is, the calculated n-th 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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