Unmanned aerial vehicle aeromagnetic survey real-time inversion method and system

Abstract

The application provides a UAV aeromagnetic survey real-time inversion method and system, relates to the field of geophysics, and the method comprises the following steps: grid dissection is performed on the underground space of a target region to obtain various dissection grids; a weighted matrix used for inversion is calculated according to the position information of the dissection grids; aeromagnetic data of a current observation point are acquired in real time and preprocessed to obtain magnetic anomaly data; a kernel vector is calculated according to the position information of the current observation point; the kernel vector is incorporated into a kernel matrix; an initial model of the current observation point is determined by using a real-time inversion magnetic body model obtained by using a previous observation point; real-time inversion is performed by using the initial model, the weighted matrix and the kernel matrix, a real-time inversion magnetic body model of the current observation point is obtained, visual display is performed, and real-time imaging of the magnetic distribution result of the underground space is completed. The technical scheme of the application realizes the function of real-time and rapid inversion under the condition of ensuring inversion accuracy.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of geophysics, in particular to a real-time inversion method and system for unmanned aerial vehicle (UAV) airborne magnetic survey. BACKGROUND

[0002] The UAV airborne magnetic survey is a fast, efficient and economical geophysical exploration method. The magnetic anomaly inversion is performed on the airborne magnetic data obtained by the UAV survey, and the magnetic body field source distribution is obtained, which is of great significance for the detection and positioning of concealed target bodies.

[0003] During inversion, the underground space is divided into a plurality of discrete units, and it is assumed that the magnetization intensity or the magnetic susceptibility of each discrete unit is uniform. The kernel matrix is calculated, the observed magnetic anomaly data is input, and the magnetization intensity or the magnetic susceptibility distribution of the underground space can be calculated through inversion.

[0004] At present, the airborne magnetic anomaly inversion is usually performed after the completion of the airborne magnetic survey, and the data measurement and data inversion are independent, which leads to the fact that the airborne magnetic anomaly observation results cannot be evaluated in a timely manner, and the inversion results cannot be obtained in real time, which is not conducive to improving the detection efficiency and accuracy. SUMMARY

[0005] The purpose of the present application is to solve the problem that the existing airborne magnetic anomaly inversion method cannot perform real-time inversion on the measured airborne magnetic data, and cannot balance the detection efficiency and detection accuracy. A real-time inversion method and system for unmanned aerial vehicle (UAV) airborne magnetic survey are provided.

[0006] The above-mentioned purpose of the present application is achieved by the following technical solutions:

[0007] S1: performing grid division on the underground space of the target area to obtain each divided grid;

[0008] S2: calculating a weighted matrix for inversion according to the position information of the divided grid;

[0009] S3: obtaining the airborne magnetic data of the current observation point in real time and performing preprocessing to obtain the magnetic anomaly data;

[0010] S4: calculating a kernel vector according to the position information of the current observation point; and incorporating the kernel vector into a kernel matrix;

[0011] S5: determining an initial model of the current observation point by using the real-time inversion magnetic body model obtained by the previous observation point; performing real-time inversion by using the initial model, the weighted matrix and the kernel matrix to obtain the real-time inversion magnetic body model of the current observation point and perform visual display, and completing real-time imaging of the magnetic distribution result of the underground space.

[0012] Optionally, step S3 comprises:

[0013] Preprocessing includes compensation, correction and filtering.

[0014] Optionally, step S4 includes:

[0015] The kernel matrix is ​​as follows:

[0016]

[0017] In the formula For the The kernel matrix of the real-time inversion of observation points, The observation point is the current observation point; For the The kernel matrix of the real-time inversion of observation points, The observation point is the previous observation point; For the The kernel vector of the real-time inversion of each observation point is used to calculate the magnetic anomaly response of the grid of unit size magnetization intensity or magnetic susceptibility to the current observation point.

[0018] Optionally, step S5 includes:

[0019] S51: Set up The initial model of the observation point is , Equal to Real-time inversion of magnetic body model at each observation point times, that is ,in ;

[0020] S52: Using the initial model And the kernel matrix is ​​inverted in real time to obtain the Real-time inversion magnetic body model of each observation point;

[0021] S53: Visualize the real-time inversion magnetic body model to complete the real-time imaging of the magnetic distribution results of the underground space.

[0022] Optionally, step S52 includes:

[0023] S52a:Set ;like ,but ,otherwise ;

[0024] S52b: Calculation ,in represents aeromagnetic observation data, Indicates the The fitted data after iterations, Indicates the data residual after sub-iteration;

[0025] S52c: if the error is less than a preset error , output the optimal solution , and obtain a real-time inversion magnetic body model;

[0026] if , execute step S52d;

[0027] S52d: let , where denotes a model increment of the i-th iteration;

[0028] S52e: let , where denotes a weighted iteration direction, denotes a weighting matrix used for inversion, if , let , otherwise let , , denotes an iteration step length;

[0029] S52f: let

[0030]

[0031]

[0032]

[0033]

[0034] where denotes an intermediate variable of the iteration process, denotes an iteration step length;

[0035] S52g: if the error is less than a preset error , execute step S52h;

[0036] if , let , and execute step S52e;

[0037] S52h: , apply upper and lower bound constraints to , i.e. , the distribution represents a minimum value and a maximum value of the upper and lower bound constraints;

[0038] let ​, execute step S52b.

[0039] A real-time inversion system for UAV aeromagnetic measurement, comprising: a data acquisition module, a data preprocessing module, an inversion module, and a display module;

[0040] The data acquisition module, data preprocessing module, inversion module and display module are connected in sequence;

[0041] The data acquisition module is used to obtain the aeromagnetic data of the current observation point in real time;

[0042] The data preprocessing module is used to preprocess the aeromagnetic data to obtain magnetic anomaly data;

[0043] The inversion module is used to perform grid division on the underground space of the target area to obtain various grid divisions;

[0044] The inversion module is further used to calculate a weighted matrix for inversion based on position information of the subdivided grid;

[0045] The inversion module is further used to calculate the kernel vector according to the position information of the current observation point; and incorporate the kernel vector into the kernel matrix;

[0046] The inversion module is further used to determine the initial model of the current observation point through the real-time inversion magnetic body model obtained at the previous observation point; perform real-time inversion through the initial model, weighting matrix and kernel matrix to obtain the real-time inversion magnetic body model of the current observation point;

[0047] The display module is used to visualize the real-time inversion magnetic body model and complete the real-time imaging of the magnetic distribution results of the underground space.

[0048] Optionally, the data acquisition module includes: a drone and a magnetometer;

[0049] The magnetometer is arranged on the UAV;

[0050] The magnetometer is used to obtain aeromagnetic data of the current observation point.

[0051] A computer-readable storage medium stores instructions. When the instructions are executed, a real-time inversion method for unmanned aerial vehicle aeromagnetic measurement is performed.

[0052] The beneficial effects of the technical solution provided by this application are:

[0053] The present application provides a method for real-time inversion in the process of unmanned aerial vehicle (UAV) airborne magnetic surveying, which can update the kernel matrix immediately after the UAV airborne magnetic system completes the measurement of the magnetic data of a survey point, and then iteratively inverts the real-time inversion model obtained after the observation of the previous survey point as the initial model to obtain the real-time inversion model of the current survey point and visually display the model, so as to evaluate the magnetic anomaly observation results in real time and improve the efficiency and accuracy of the UAV airborne magnetic surveying. BRIEF DESCRIPTION OF DRAWINGS

[0054] The present application will be further described below in combination with the drawings and embodiments, wherein:

[0055] Figure 1 is a flowchart in the embodiments of the present application;

[0056] Figure 2 is a system module diagram in the embodiments of the present application;

[0057] Figure 3 is a magnetization distribution diagram in the embodiments of the present application;

[0058] Figure 4 is a real-time inversion result diagram of the 10th data in the embodiments of the present application;

[0059] Figure 5 is a real-time inversion result diagram of the 20th data in the embodiments of the present application;

[0060] Figure 6 is a real-time inversion result diagram of the 30th data in the embodiments of the present application;

[0061] Figure 7 is a real-time inversion result diagram of the 40th data in the embodiments of the present application;

[0062] Figure 8 is a real-time inversion result diagram of the 50th data in the embodiments of the present application. DETAILED DESCRIPTION

[0063] In order to have a clearer understanding of the technical features, objects and effects of the present application, the specific embodiments of the present application will be described in detail with reference to the drawings.

[0064] The embodiments of the present application provide a real-time inversion method for UAV airborne magnetic surveying.

[0065] Please refer to Figure 1 , Figure 1 is a flowchart of a real-time inversion method for UAV airborne magnetic surveying in the embodiments of the present application, which comprises:

[0066] S1: performing grid division on the underground space of a target area to obtain each divided grid;

[0067] S2: Calculate the weight matrix for inversion based on the position information of the subdivided grid;

[0068] S3: Acquire the aeromagnetic data of the current observation point in real time and perform preprocessing to obtain magnetic anomaly data;

[0069] Step S3 includes:

[0070] Preprocessing includes compensation, correction and filtering.

[0071] As an embodiment, aeromagnetic data of an observation point is collected by a drone, and the aeromagnetic data is sequentially input into a compensation system, a correction system, and a filtering system to obtain corrected magnetic anomaly data.

[0072] S4: Calculate the kernel vector based on the position information of the current observation point; incorporate the kernel vector into the kernel matrix;

[0073] Step S4 includes:

[0074] The kernel matrix is ​​as follows:

[0075]

[0076] In the formula For the The kernel matrix of the real-time inversion of observation points, The observation point is the current observation point; For the The kernel matrix of the real-time inversion of observation points, The observation point is the previous observation point; For the The kernel vector of the real-time inversion of each observation point is used to calculate the magnetic anomaly response of the grid of unit size magnetization intensity or magnetic susceptibility to the current observation point.

[0077] S5: Determine the initial model of the current observation point through the real-time inversion magnetic body model obtained from the previous observation point; perform real-time inversion through the initial model, weighted matrix, and kernel matrix to obtain the real-time inversion magnetic body model of the current observation point and perform visualization to complete the real-time imaging of the magnetic distribution results of the underground space.

[0078] Step S5 includes:

[0079] S51: Set up The initial model of the observation point is , Equal to Real-time inversion of magnetic body model at each observation point times, that is ,in ;

[0080] S52: Using the initial model And the kernel matrix is ​​inverted in real time to obtain the Real-time inversion magnetic body model of each observation point;

[0081] Step S52 includes:

[0082] S52a:Set ;like ,but ,otherwise ;

[0083] S52b: Calculation ,in represents aeromagnetic observation data, Indicates the The fitted data after iterations, Indicates the The data residual after iterations;

[0084] S52c: If Less than the preset error , then output the optimal solution , get the real-time inversion magnetic body model;

[0085] like , then execute step S52d;

[0086] S52d: Order ,in Indicates the The model increment of the iteration;

[0087] S52e: Order ,in represents the weighted iteration direction, represents the weighting matrix used for inversion, ;like , then let , otherwise let , , represents the iteration step size;

[0088] S52f: Command

[0089]

[0090]

[0091]

[0092]

[0093] in represents the intermediate variables of the iterative process, represents the iteration step size;

[0094] S52g: If Less than the preset error , execute step S52h;

[0095] like , then let , execute step S52e;

[0096] S52h: ,right Apply upper and lower bound constraints, i.e. , The distribution represents the minimum and maximum values ​​of the upper and lower bounds;

[0097] make , execute step S52b.

[0098] S53: Visualize the real-time inversion magnetic body model to complete the real-time imaging of the magnetic distribution results of the underground space.

[0099] Please refer to Figure 2 , Figure 2 This is a module diagram of a real-time inversion system for UAV aeromagnetic measurement in an embodiment of the present application, wherein the system includes: a data acquisition module, a data preprocessing module, an inversion module, and a display module;

[0100] The data acquisition module, data preprocessing module, inversion module and display module are connected in sequence;

[0101] The data acquisition module is used to obtain the aeromagnetic data of the current observation point in real time;

[0102] The data preprocessing module is used to preprocess the aeromagnetic data to obtain magnetic anomaly data;

[0103] The inversion module is used to perform grid division on the underground space of the target area to obtain various grid divisions;

[0104] The inversion module is further used to calculate a weighted matrix for inversion based on position information of the subdivided grid;

[0105] The inversion module is further used to calculate the kernel vector according to the position information of the current observation point; and incorporate the kernel vector into the kernel matrix;

[0106] The inversion module is further used to determine the initial model of the current observation point through the real-time inversion magnetic body model obtained at the previous observation point; perform real-time inversion through the initial model, weighting matrix and kernel matrix to obtain the real-time inversion magnetic body model of the current observation point;

[0107] The display module is used to visualize the real-time inversion magnetic body model and complete the real-time imaging of the magnetic distribution results of the underground space.

[0108] The data acquisition module includes: a drone and a magnetometer;

[0109] The magnetometer is arranged on the UAV;

[0110] The magnetometer is used to obtain aeromagnetic data of the current observation point.

[0111] As an example, let the total number of drone aeromagnetic observation points be The measurement interval is 20 m, and the total length of the required measurement section is 1000 m. The specific steps of real-time inversion are:

[0112] Step 1: Divide the underground space into 50 × 25 = 1250 rectangular grid units, each of which is 20 m × 20 m in size. ;

[0113] Step 2: Using the position information of the mesh , calculate the weight matrix P:

[0114]

[0115] Where C is a constant used to adjust the weight matrix value, is the magnetic anomaly decay rate constant; Represents the identity matrix.

[0116] Step 3: Acquire the aeromagnetic data of the current observation point in real time and preprocess it to obtain magnetic anomaly data; calculate the kernel vector based on the position information of the current observation point; and incorporate the kernel vector into the kernel matrix;

[0117] Step 4: Let the current Initial model at observation points Equal to the previous real-time inversion result times, that is , Take 0.9, if at this time ,Pick Using the initial model Constrain the previous real-time inversion result and calculate the smooth solution of the model The maximum number of iterations is set to 20, and the allowable error and Set to 0.001 and 0.01, set the maximum allowed magnetization intensity to 100 A / m and the minimum to 0 A / m.

[0118] Step 5: Display real-time inversion results ,make And return to step 3.

[0119] As an example, Figure 3 is the distribution diagram of the real magnetization intensity; Figure 4 Measure the 10th data for the drone ( = 200 m) after compensation, correction and filtering of the total field measurement data and the results of real-time inversion; Figure 5 Measure the 20th data for the drone ( = 400 m) after compensation, correction and filtering of the total field measurement data and the results of real-time inversion; Figure 6 Measure the 30th data for the drone ( = 600 m) after compensation, correction and filtering of the total field measurement data and the results of real-time inversion; Figure 7 Measure the 40th data for the drone ( = 800 m) after compensation, correction and filtering of the total field measurement data and the results of real-time inversion; Figure 8 When the drone measurement is completed (the 50th data, = 1000 m) total field measurement data after compensation, correction and filtering and real-time inversion results; the present invention can perform real-time magnetic anomaly inversion based on the observed magnetic anomaly data.

[0120] As an example, Figure 5 As shown in the figure, when the drone measurement data is incomplete but sufficient, the method of this patent invention can obtain inversion results close to the real geological model. It can be seen that the real-time inversion method of drone aeromagnetic anomaly data in this application realizes the function of real-time rapid inversion while ensuring the accuracy of inversion, which is conducive to the real-time evaluation of drone-observed magnetic anomalies, and the real-time adjustment and optimization of the drone observation system, thereby improving the efficiency and accuracy of drone aeromagnetic detection.

[0121] The present application also discloses a computer-readable storage medium storing a plurality of instructions suitable for loading by a processor to execute the above-mentioned real-time inversion method for UAV aeromagnetic measurement.

[0122] The above are merely exemplary embodiments of the present disclosure and are not intended to limit the scope of the present disclosure. In other words, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure.

[0123] This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not described herein. The description and examples are to be considered as exemplary only, and the scope and spirit of the present disclosure are to be defined by the claims.

Claims

1. A real-time inversion method for UAV aeromagnetic measurement, characterized in that: The method comprises the following steps: S1: Gridding the underground space of the target area to obtain various grids; S2: Calculate the weight matrix for inversion based on the position information of the subdivided grid; S3: Acquire the aeromagnetic data of the current observation point in real time and perform preprocessing to obtain magnetic anomaly data; S4: Calculate the kernel vector based on the position information of the current observation point; incorporate the kernel vector into the kernel matrix; S5: Determine the initial model of the current observation point through the real-time inversion magnetic body model obtained from the previous observation point; perform real-time inversion through the initial model, weighted matrix, and kernel matrix to obtain the real-time inversion magnetic body model of the current observation point and perform visualization to complete the real-time imaging of the magnetic distribution results of the underground space.

2. The real-time inversion method for UAV aeromagnetic measurement according to claim 1, characterized in that: Step S3 includes: Preprocessing includes compensation, correction and filtering.

3. The real-time inversion method for UAV aeromagnetic measurement according to claim 1, characterized in that: Step S4 includes: The kernel matrix is ​​as follows: Where G k is the kernel matrix of the real-time inversion of the k-th observation point, and the k-th observation point is the current observation point; G k-1 is the kernel matrix of the real-time inversion of the k-1th observation point, where the k-1th observation point is the previous observation point; g k It is the kernel vector of the real-time inversion of the k-th observation point, that is, the magnetic anomaly response of the grid with unit size magnetization intensity or magnetic susceptibility to the current observation point.

4. The real-time inversion method for UAV aeromagnetic measurement according to claim 3, characterized in that: Step S5 includes: S51: Assume that the initial model of the k-th observation point is Equal to Ω times the real-time inversion magnetic body model of the k-1th observation point, that is, where Ω∈[0, 0.9]; S52: Using the initial model And the kernel matrix is ​​used for real-time inversion to obtain the real-time inversion magnetic body model of the k-th observation point; S53: Visualize the real-time inversion magnetic body model to complete the real-time imaging of the magnetic distribution results of the underground space.

5. The real-time inversion method for UAV aeromagnetic measurement according to claim 4, characterized in that: Step S52 includes: S52a: Let i = 0; if k = 1, then otherwise S52b: Calculation Δd i =dd i , where d represents the aeromagnetic observation data, d i represents the fitting data after the i-th iteration, Δd i Represents the data residual after the i-th iteration; S52c: If ||Δd i || is less than the preset error ε, then the optimal solution is output Obtain real-time inversion magnetic body model; If ||Δd i ||≥ε, then execute step S52d; S52d: Let Δm i =0,j=0,r j =(G k ) T Δd i , where Δm i represents the model increment of the i-th iteration; S52e: Order z j =Pr j , where z j represents the weighted iteration direction, P represents the weighting matrix used for inversion, r j Indicates the iteration direction; if j = 0, then let p j =z j , otherwise let p j =z j +α j-1 p j-1 , α j-1 represents the iteration step size; S52f: Command H j =(G k ) T G k p j Δm i =Δm i +t j p j r j+1 =r j -t j H j Among them H j Represents the intermediate variable of the iterative process, t j represents the iteration step size; S52g: If || p j ||Less than the preset error ε PCG , execute step S52h; If ||p j ||≥ε PCG , then let j=j+1 and execute step S52e; S52h: right Apply upper and lower bound constraints, i.e. m min 、m max The distribution represents the minimum and maximum values ​​of the upper and lower bounds; Let i=i+1 and execute step S52b.

6. A real-time inversion system for UAV aeromagnetic measurement, used to implement a real-time inversion method for UAV aeromagnetic measurement according to any one of claims 1 to 5, characterized in that: The system includes: a data acquisition module, a data preprocessing module, an inversion module and a display module; The data acquisition module, data preprocessing module, inversion module and display module are connected in sequence; The data acquisition module is used to obtain the aeromagnetic data of the current observation point in real time; The data preprocessing module is used to preprocess the aeromagnetic data to obtain magnetic anomaly data; The inversion module is used to perform grid division on the underground space of the target area to obtain various grid divisions; The inversion module is further used to calculate a weighted matrix for inversion based on position information of the subdivided grid; The inversion module is further used to calculate the kernel vector according to the position information of the current observation point; and incorporate the kernel vector into the kernel matrix; The inversion module is further used to determine the initial model of the current observation point through the real-time inversion magnetic body model obtained at the previous observation point; perform real-time inversion through the initial model, weighting matrix and kernel matrix to obtain the real-time inversion magnetic body model of the current observation point; The display module is used to visualize the real-time inversion magnetic body model and complete the real-time imaging of the magnetic distribution results of the underground space.

7. The real-time inversion system for UAV aeromagnetic measurement according to claim 6, characterized in that: The data acquisition module includes: a drone and a magnetometer; The magnetometer is arranged on the UAV; The magnetometer is used to obtain aeromagnetic data of the current observation point.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores instructions, and when the instructions are executed by a computer, the method according to any one of claims 1 to 5 is executed.

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