A method for airborne fixed-point compensation of carrier interference based on magnetic tensor

Abstract

The present invention discloses an aerial fixed-point compensation method for carrier interference based on magnetic tensors, comprising: establishing a carrier interference magnetic field calculation model based on a magnet simulation method, establishing a mathematical mapping relationship between carrier posture changes and parameters such as the spatial position and volume of ferromagnetic bodies in the carrier and the interference magnetic field; constructing a linear compensation model for the interference of the carrier magnetic tensor contraction amount, and suppressing the interference of the carrier magnetic tensor contraction amount; designing an aerial fixed-point maneuvering compensation method for unmanned aerial vehicles, using an optimization algorithm to calculate the compensation coefficient, and reducing the requirements of the compensation flight method for a large-scale uniform magnetic field environment.

Description

Technical Field

[0001] The present invention belongs to the field of geophysical exploration technology, and in particular relates to an aerial fixed-point compensation method for carrier interference based on magnetic tensor. Background Art

[0002] As a highly effective geophysical exploration method, aeromagnetic surveying is widely used in fields such as unexploded ordnance detection and resource exploration. However, magnetic field interference generated by the ferromagnetic materials of the aerial carrier platform can significantly degrade the signal quality of the measured target, seriously hindering the interpretation of magnetic survey data. Therefore, carrier magnetic compensation is a key technology in aeromagnetic surveying.

[0003] There are some defects in the existing technology that cannot be ignored: (1) The existing carrier magnetic interference model is mainly the TL model, which expresses the carrier's magnetic field interference through the linear combination approximation method. It is difficult to establish a quantitative relationship between the carrier's magnetic field interference and its attitude change, the spatial position of the ferromagnetic body, the volume of the ferromagnetic body and other parameters, which increases the difficulty in analyzing the carrier's magnetic field interference characteristics and the difficulty in establishing the carrier's magnetic interference compensation model. (2) Multi-rotor drones have become the mainstream platform for aeromagnetic exploration due to their high maneuverability. The existing flight compensation method is limited by the shortcomings of fixed-wing aircraft's poor maneuverability and requires a large range of uniform magnetic field environment, which is difficult to meet the actual application requirements. (3) The compensation model in the existing technology is mainly used to compensate for the carrier's magnetic field scalar. However, as vector magnetometer arrays have become the mainstream magnetic measurement equipment due to their ability to resist time-varying interference, researchers prefer to use vector magnetometer array measurements. The traditional method exposes a fundamental contradiction and is difficult to compensate for the magnetic tensor contraction generated by the carrier, which seriously restricts the application of magnetometer arrays in aeromagnetic exploration. Summary of the Invention

[0004] The present invention proposes an aerial fixed-point compensation method for carrier interference based on magnetic tensor to solve the problem that traditional aeromagnetic compensation methods are only applicable to carrier scalar magnetic field interference compensation, cannot be adapted to airborne magnetic measurement systems equipped with vector magnetometer arrays, and rely on a large-scale uniform magnetic field environment.

[0005] The technical solution for achieving the purpose of the present invention is: a method for airborne fixed-point compensation of carrier interference based on magnetic tensor, comprising:

[0006] A carrier magnetic field interference model is established based on the mathematical mapping relationship between attitude changes, the spatial position of ferromagnetic bodies in the UAV carrier and magnetic field interference;

[0007] Based on the carrier magnetic field interference model, a carrier magnetic tensor contraction and interference compensation model is established;

[0008] The UAV performs a compensation maneuver at a fixed point in the air and obtains magnetic field data measured by each magnetometer in a vector magnetometer array installed on the UAV carrier;

[0009] The magnetic field data measured by each magnetometer in the vector magnetometer array is combined with the scalar data of the Earth's magnetic field to calculate the projection of the background magnetic field at the position of the i-th magnetometer in the vector magnetometer array on the three axes;

[0010] The projection of the background magnetic field on the three axes at the position of the i-th magnetometer in the vector magnetometer array is input into the carrier magnetic tensor contraction interference compensation model. At the same time, the optimization algorithm is used to calculate the compensation coefficient in the carrier magnetic tensor contraction interference compensation model to achieve magnetic compensation.

[0011] Compared with the existing technology, the present invention has the following significant advantages: the present invention realizes the carrier interference fixed-point flight compensation in the air by establishing a carrier magnetic tensor contraction interference compensation model, and the compensation effect is significantly better than the existing supplementary method; at the same time, a UAV aerial fixed-point maneuvering compensation method is designed, and the compensation coefficient is calculated by an optimization algorithm, which reduces the requirements of the compensation flight method for a large-scale uniform magnetic field environment.

[0012] The present invention will be described in further detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 This is a flow chart of a method for aerial fixed-point compensation of carrier interference based on magnetic tensor in Example 1 of the present invention.

[0014] Figure 2 Schematic diagram of carrier magnetic interference in an embodiment of the present invention.

[0015] Figure 3 Schematic diagram of the structure of the magnetometer array carried by the carrier in an embodiment of the present invention.

[0016] Figure 4 3 is a comparison diagram of the interference between the carrier magnetic tensor contraction and the amount of interference before and after compensation in Example 1 of the present invention.

[0017] Figure 5 This is a schematic diagram of the carrier ferromagnetic interference simulation parameter settings in the second embodiment of the present invention.

[0018] Figure 6 3 is a graph showing the change of attitude angle over time in the second embodiment of the present invention.

[0019] Figure 7 This is a schematic diagram of the conventional compensation flight path for the non-uniform background magnetic field in the third embodiment of the present invention. DETAILED DESCRIPTION

[0020] A method for airborne fixed-point compensation of carrier interference based on magnetic tensor, the method comprising the following steps:

[0021] Step 1: Establish a carrier magnetic field interference model based on the magnet simulation method. The carrier magnetic field interference model is established based on the mathematical mapping relationship between posture change, the spatial position of the ferromagnetic body in the carrier, the volume of the ferromagnetic body, magnetic parameters and magnetic field interference. The specific process is as follows:

[0022] The UAV carrier is divided into m interference sources, and the magnetic moment of the i-th interference source is expressed as:

[0023] (1)

[0024] in, , is the magnetic susceptibility of the i-th interference source, 、 、 are the demagnetization coefficients of the i-th interference source in the l, t, and v directions, respectively. The l direction is along the direction of the machine arm, the t direction is perpendicular to the l direction, and the v direction is perpendicular to the plane enclosed by the l and t directions. The demagnetization coefficient is related to the shape, material and other characteristics of the interference source and can be calculated by finite element simulation software; is the volume of the ferromagnet; , is the Euler rotation matrix; for They are all projections of the Earth's magnetic field on the carrier coordinate system at 0°. , are the rotation angles of the UAV carrier around the three directions of l, t, and v respectively; is the residual magnetization intensity of the i-th interference source, .

[0025] Calculate the carrier's magnetometer position P at the kth k The magnetic field B generated at pk , that is, the carrier magnetic field interference model, specifically the superposition of the magnetic fields of all ferromagnetic interference sources on the carrier:

[0026] (2)

[0027] In the formula , is the vacuum permeability, ; is the distance between the i-th ferromagnetic interference source and the k-th magnetometer; ( , , ) is the x, y, z axis coordinate of the kth magnetometer; ( , , ) are the x-, y-, and z-axis coordinates of the i-th ferromagnetic interference source, and m is the number of interference sources.

[0028] Calculate the magnetic field measured by the kth magnetometer :

[0029]

[0030] in, The rotation matrix that transforms the carrier coordinate system to the sensor coordinate system.

[0031] Step 2: Based on the carrier magnetic field interference model in step 1, a carrier magnetic tensor contraction and merging interference compensation model is established, specifically:

[0032] (3)

[0033] Where, is the interference of the carrier magnetic tensor contraction measured in the vector magnetometer array, is the compensation coefficient matrix; is the parameter matrix related to the Earth’s magnetic field, , n is the number of vector magnetometers in the array;

[0034] , , , ,

[0035] H ekx , H eky , H ekz They represent the projections of the background magnetic field at the k-th magnetometer position on the x, y, and z axes, respectively. , is the magnetic field measured by the k-th magnetometer, k=1,2,3…n, is the size of the background magnetic field, and the local background magnetic field can be obtained by a scalar magnetometer.

[0036] Step 3: The UAV performs a compensation maneuver at a fixed point in the air (the UAV carrier yaw angle is 0 to 360 degrees, the pitch angle is -15 to 15 degrees, and the roll angle is -15 to 15 degrees). Preferably, the maneuver is a uniform motion with a yaw angle of 0 to 360 degrees, and the pitch angle and roll angle are sinusoidal motions within the range of ±5 degrees to obtain the magnetic field data measured by each magnetometer in the vector magnetometer array. .

[0037] Step 4: Combine the magnetic field data measured by each magnetometer in the vector magnetometer array obtained in step 3 with the scalar data of the Earth's magnetic field. , calculate the projection H of the background magnetic field on the x, y, and z axes at the position of the i-th magnetometer in the vector magnetometer array ekx , H eky , H ekz .

[0038] Step 5: The projection H of the background magnetic field at the position of the i-th magnetometer in the vector magnetometer array in step 4 on the x, y, and z axes is calculated. eix , H eiy , H eiz The input is fed into the interference compensation model of the carrier magnetic tensor contraction and merging, and the compensation coefficient in the model is calculated by the optimization algorithm to achieve magnetic compensation. The objective function of the compensation coefficient of the carrier magnetic tensor contraction and merging interference compensation model using the optimization algorithm is as follows:

[0039] (4)

[0040] Where d represents the sampling point number (d=1,2,3…,N), and N is the total number of sampling points. a is a 91-dimensional compensation coefficient matrix. Constructed for the magnetic field data at the d-th sampling point Parameter matrix.

[0041] The present invention solves the technical problems that traditional aeromagnetic compensation methods require a large-scale uniform magnetic field environment, are only applicable to carrier scalar magnetic field interference compensation, and cannot be adapted to aeromagnetic anomaly detection systems equipped with vector magnetometer arrays.

[0042] Simulation and experiments show that, ① in the non-uniform background magnetic field, the designed air fixed-point hovering compensation method has better compensation effect than the traditional method, and the improvement ratio is increased by about 6 times. ② A carrier C T The linear compensation model of interference makes the compensation carrier C T The interference standard deviation is reduced to 0.006% of that before compensation. The present invention has important significance for magnetic compensation of an aeronautical magnetic anomaly detection system equipped with a vector magnetometer array.

[0043] A more detailed description will be given with reference to the embodiments.

[0044] like Figure 1 As shown, this embodiment provides a method for airborne fixed-point compensation of carrier interference based on magnetic tensor, and verifies its compensation effect through experiments. Figure 1 .

[0045] S1, construct a carrier magnetic field interference model based on multiple dipoles:

[0046] S1.1, Coordinate System Definition:

[0047] Establish as Figure 2 In the coordinate system shown, the l-axis is along the direction of the machine arm, the t-axis is perpendicular to the l-axis, and the v-axis is perpendicular to the plane enclosed by the l-axis and the t-axis.

[0048] S1.2, Interference source decomposition:

[0049] Ignore the carrier's eddy current magnetic field interference (due to the small conductor area of the drone and the low rate of magnetic field change under stable operating conditions), and only consider soft and hard magnetic interference. The soft and hard magnetic interference materials of the unmanned platform are divided into n magnetic dipole interference sources.

[0050] S1.3, Magnetic moment calculation:

[0051] If the carrier platform rotates around the three axes l, t, and v respectively , , the right-hand rule is followed during rotation, and the magnetic moment generated by the i-th ferromagnetic interference source is :

[0052] (5)

[0053] in, , is the magnetic susceptibility of the i-th interference source, , , are the demagnetization coefficients of the i-th interference source in the l, t, and v directions respectively. These three parameters are related to the shape, material and other characteristics of the interference source and can be calculated by finite element simulation software. V is the volume of the ferromagnetic body. , is the Euler rotation matrix; for , They are all projections of the Earth's magnetic field on the carrier coordinate system at 0°. ; is the residual magnetization intensity of the i-th interference source, .

[0054] S1.4, Magnetic Field Calculation:

[0055] The i-th ferromagnetic interference source is located at P 0i (x 0i , y 0i , z 0i ), which is at the kth magnetometer position P k (x k , y k , z k ) It can be expressed as:

[0056] (6)

[0057] In the formula , is the vacuum permeability, ; is the distance between the i-th ferromagnetic interference source and the k-th magnetometer; x k ,yk ,y k , are the x, y, and z axis coordinates of the kth magnetometer respectively; x 0i ,y 0i ,y 0i , are the x-, y-, and z-axis coordinates of the i-th ferromagnetic interference source.

[0058] S1.5, calculation of the total interference magnetic field of the UAV carrier:

[0059] The carrier is at the kth magnetometer position P k The magnetic field generated at Superposition of the magnetic fields of all ferromagnetic interference sources (the total number of interference sources is m):

[0060] (7)

[0061] S2, built based on magnetic interference model Compensation Model:

[0062] S2.1, vector magnetometer array:

[0063] A simplified diagram of the vector magnetometer array is shown in Figure 3 As shown, the magnetometer array consists of four fluxgates, the coordinate origin is at the center of the vector magnetometer array, the x-axis is along the direction from sensor 1 to 2, the y-axis is along the direction from magnetometer 3 to 2, and the z-axis is perpendicular to the magnetometer array plane and upward.

[0064] S2.2, Magnetic Gradient Tensor Calculation:

[0065] The magnetic field measured by the kth magnetometer :

[0066] (8)

[0067] in, The rotation matrix for transforming the carrier coordinate system to the sensor coordinate system;

[0068] is the coefficient matrix related to the position, size, and magnetic parameters of the ferromagnetic interference source, ;

[0069] is the background magnetic field at the k-th magnetometer position, ; is the parameter matrix related to the remanence of the interference source, .

[0070] Calculate the magnetic gradient tensor matrix from array differences :

[0071] (9)

[0072] Component of the magnetic gradient tensor in the x direction and the y-direction magnetic gradient tensor component :

[0073] (10)

[0074] Where, , ; dx, dy are the baseline lengths of the array x and y axes, respectively, dx, dy = 0.8m; 、 、 、 is the measurement value of each magnetometer. According to the symmetry of the tensor matrix and the trace is 0, the magnetic tensor in the z direction can be calculated .

[0075] (11)

[0076] S2.3, Magnetic tensor contraction:

[0077] The magnetic tensor contraction amount obtained by array measurement :

[0078] (12)

[0079] S2.4, Compensation Model:

[0080] Building a compensation model

[0081] (13)

[0082] Where, is the interference of the carrier magnetic tensor contraction measured by the array, is the compensation coefficient matrix; is the parameter matrix related to the background magnetic field, , n is the number of magnetometers in the array;

[0083] , , , ,

[0084] H ekx , H eky , H ekz They represent the projections of the background magnetic field at the k-th magnetometer position on the x, y, and z axes, respectively. , is the magnetic field measured by the k-th magnetometer, k=1,2,3…n, is the size of the background magnetic field, and the local background magnetic field can be obtained by a scalar magnetometer.

[0085] S3, perform fixed-point compensation flight in the air to obtain magnetic field data:

[0086] Experimental setup:

[0087] Platform: Hexacopter drone (15kg payload, 5m / s speed)

[0088] Sensors: Cesium optically pumped magnetometer for background magnetic field measurement; fluxgate array; inertial navigation module for obtaining and measuring drone attitude angle and position data.

[0089] 2 Compensation Flight Process

[0090] Maneuvering: The drone hovers at an altitude of 100m and rotates around its three axes l, t, and v (α, β∈[−5°, 5°], γ∈[0°, 360°])

[0091] Data collection: Perform two sets of compensation flights (training set and validation set), each taking ≤30s, and collect sensor data

[0092] S4, substitute the magnetic field data into the compensation model and use the optimization algorithm to obtain the compensation coefficient matrix

[0093] Substitute the collected fluxgate data and background magnetic field into the compensation model, and use Levenberg-Marquardt to solve the compensation coefficient matrix;

[0094] S5, inputting the compensation coefficient and magnetic field data into the compensation model to achieve magnetic compensation;

[0095] The compensation coefficient matrix obtained in S4 The magnetic field data in step S3 is substituted into the compensation model to obtain the compensated magnetic interference. The magnetic interference before and after compensation is as follows: Figure 4 As shown. After compensation, C T The standard deviation was reduced to 0.006%~0.007% before compensation, verifying the effectiveness of the method. The specific data are shown in Table 1.

[0096] Table 1

[0097]

[0098] Example 2: Carrier Magnetic Interference Modeling and Accuracy Verification

[0099] Implementation Purpose

[0100] This example provides a method for modeling carrier magnetic interference and compares it with the carrier magnetic field interference calculated by finite element simulation software. This verifies the accuracy of the carrier magnetic interference modeling based on the magnet simulation method. By comparing the finite element simulation results, the model's predictive ability under complex postures is evaluated. The specific implementation steps are as follows:

[0101] Simulation settings:

[0102] 1. Parameter settings

[0103] The number of ferromagnetic interference sources on the UAV carrier is 7, the magnetic permeability of the interference source is 200, and the shape is a cuboid with a length of 0.2 m, a width of 0.1 m, and a height of 0.05 m. Figure 5 In the coordinate system shown, the center of interference source 7 is at the origin (0, 0, 0) m. The coordinates of interference sources 1 to 6 are (1, 0, 0) m, (0.5, 0.84, 0) m, (-0.5, 0.84, 0) m, (-1, 0, 0) m, (-0.5, -0.87, 0) m, and (0.5, -0.87, 0) m, respectively. The residual magnetization intensity of the interference source is along the direction of the Earth's magnetic field and is 100 A / m. The four fluxgate coordinates are (-0.4, 0.4, -1) m, (0.4, 0.4, -1) m, (0.4, -0.4, -1) m, and (-0.4, -0.4, -1) m. Background magnetic field The attitude angle of the drone changes as follows: Figure 6 As shown in the figure, γ varies from 0 to 360°, β varies from -5 to 5°, and α varies from -5 to 5°. In the simulation, the directions of the magnetometer's x, y, and z axes are consistent with the directions of the carrier's l, t, and v axes.

[0104] 2. Simulation process:

[0105] Finite element simulation:

[0106] Select the "Magnetic Field, No Current" module in the finite element software; import the drone model and set the material properties; then calculate the projection component of the geomagnetic field on the drone carrier coordinate system as the background magnetic field based on the carrier attitude angle change. , , input the background magnetic field into the software. Finally, solve the model.

[0107] Carrier magnetic field interference model:

[0108] Using finite element simulation software, we calculated the demagnetization factors of the ferromagnetic interference source in the three axes of l, t, and v to be 0.0995, 0.2514, and 0.4593, respectively. Inputting the simulation parameters and demagnetization factors into the carrier magnetic interference calculation model yields the model calculation results for the carrier magnetic field interference.

[0109] Results comparison:

[0110] 1: The comparison of magnetic field results is shown in Table 2

[0111] .

[0112] Table 2

[0113]

[0114] 2: Conclusion

[0115] The maximum error of magnetic field interference at each sensor position is ≤0.88 nT; the model prediction results are highly consistent with the simulation results, verifying the effectiveness of the magnet simulation method in modeling complex carrier interference.

[0116] Example 3: Verification of the airborne fixed-point compensation method under different background magnetic fields

[0117] Implementation purpose:

[0118] This embodiment provides a carrier C based on magnetic tensor T The interference compensation model establishment process and the aerial fixed-point flight method for carrier magnetic interference compensation are used to verify the effects of the aerial compensation model and fixed-point flight compensation in uniform and non-uniform magnetic fields through numerical simulation.

[0119] Implementation steps:

[0120] S1 carrier parameter settings:

[0121] Ferromagnetic interference sources

[0122] To simplify the analysis, the number of carrier ferromagnetic interference sources is 1, and its shape is a cuboid with a length of 0.2 m, a width of 0.1 m, and a height of 0.05 m. The center coordinates are (0, 0, 0) m, and the residual magnetization intensity is 100 A / m (along the direction of the geomagnetic field).

[0123] 2 Demagnetization factor

[0124] The demagnetization factors in the three axes of l, t, and v are 0.0995, 0.2514, and 0.4593, respectively (obtained by COMSOL simulation).

[0125] 3 Magnetometer coordinate system:

[0126] The coordinate system of the vector magnetometer in the carrier coincides with the coordinate system of the carrier.

[0127] S2 Aerial fixed-point maneuvers

[0128] A total of 5 types of aerial fixed-point maneuvers were set up in the simulation.

[0129] Maneuver ①: The UAV carrier changes γ from 0° to 90° at a constant speed in the air, while β and α change sinusoidally at ±5°.

[0130] Maneuver ②: The UAV carrier changes γ from 0° to 180° at a constant speed in the air, while β and α change sinusoidally at ±5°.

[0131] Maneuver ③: The UAV carrier changes γ from 0° to 270° at a constant speed in the air, while β and α change sinusoidally at ±5°.

[0132] Maneuver ④: The UAV carrier changes γ from 0° to 360° at a constant speed in the air, while β and α change sinusoidally at ±5°.

[0133] Maneuver ⑤: When γ is 90°, β and α change sinusoidally within ±5°; when γ is 180°, β and α change sinusoidally within ±5°; when γ is 270°, β and α change sinusoidally within ±5°; when γ is 360°, β and α change sinusoidally within ±5°.

[0134] S3 Compensation Validation Dataset Generation

[0135] The specific parameters of the vehicle magnetic interference data (i.e., the validation dataset) used to verify the compensation coefficients were set as follows: the vehicle yaw angle γ was varied from 0° to 360° in 10° steps, and the pitch angle β and roll angle α were varied from -10° to 10° in 2° steps. A total of 4,477 sets of vehicle magnetic interference field data corresponding to these attitude parameters were generated. The intensity of the simulated interference field fluctuated between 32.15 and 70.23 nT / m, with a standard deviation of 10.88 nT / m.

[0136] S4 Compensation in a uniform background magnetic field

[0137] 1 Background magnetic field conditions

[0138] , The projection of the background magnetic field on the carrier coordinate system when all are 0° .

[0139] 2 Data Generation

[0140] Based on maneuvers 1 through 5, the vehicle parameters, vehicle attitude angle, and background magnetic field were input into a vehicle magnetic interference model (the model was consistent with the vehicle magnetic interference model in Example 1) to generate the magnetic field data required for compensation. Noise (Gaussian white noise with a mean of 0 nT and a variance of 0.1 nT) was added to the magnetic field data and a Monte Carlo simulation was performed, with 10,000 independent repetitions.

[0141] 3 Compensation coefficient calculation

[0142] Substitute the vector magnetometer magnetic field data and background magnetic field data into the compensation model (the compensation model is consistent with the compensation model of Example 1), and use Levenberg-Marquardt to solve the compensation coefficient matrix. The compensation coefficient matrix and the verification data set are input into the compensation model to complete the compensation of the verification data set.

[0143] 4 Evaluation Metrics

[0144] NMDS: The standard deviation ST of the interference of the carrier magnetic tensor contraction after compensation exceeds the threshold C ST The number of samples;

[0145] EMPS:NMDS / 10000.

[0146] 5 The simulation results are shown in Table 3.

[0147] Table 3

[0148]

[0149] 6 Conclusion

[0150] The compensation results of maneuvers ④ and ⑤ were good. After compensation, the sample ratios of interference standard deviations exceeding 0.01nT were 1.4% and 0%, respectively, and the sample ratios exceeding 0.03nT were both 0%.

[0151] S5 Compensation for inhomogeneous background magnetic field

[0152] 1 Background magnetic field conditions

[0153] The background magnetic field is non-uniform due to the superposition of a magnetic dipole magnetic field on the Earth's magnetic field.

[0154] Uniform background magnetic field: , The projection of the uniform background magnetic field on the carrier coordinate system when all are 0° .

[0155] Magnetic dipole interference source: The magnetic dipole moment is (0, 60000, 80000) and the position is (0, 100, 0).

[0156] 2 Comparison Schemes

[0157] Traditional flight compensation method: A quadrilateral flight compensation action is used. The length of the quadrilateral of the flight path is set to 200m. A, B, C, and D are the four endpoints of the quadrilateral, and the coordinates are (100, -100, 30)m, (-100, -100, 30)m, (-100, 100, 30)m, and (100, 100, 30)m respectively. The drone starts from point A and moves along the quadrilateral trajectory to point D. Figure 7 shown.

[0158] Aerial fixed-point compensation: The UAV performs maneuvers ① to ⑤ at the position (0, 0, 30) m.

[0159] 3 Data Generation

[0160] The carrier parameters, carrier attitude angles, and background magnetic fields in traditional compensation flight and aerial fixed-point compensation flight are respectively input into the carrier magnetic interference model (the model is consistent with the carrier magnetic field interference model in Example 1) to generate the magnetic field data required for compensation, and noise (Gaussian white noise with a mean of 0nT and a variance of 0.1nT) is added to the magnetic field data.

[0161] 4 Compensation coefficient calculation

[0162] The vector magnetometer magnetic field data and the background magnetic field data are substituted into the compensation model (the compensation model is consistent with the compensation model of the first embodiment), and the compensation coefficient matrix is solved using Levenberg-Marquardt.

[0163] The compensation coefficient matrix and the validation data set are input into the compensation model to complete the compensation of the validation data set.

[0164] 5 Comparison of compensation results

[0165] The compensation results of the traditional flight compensation method and the aerial fixed-point flight compensation method are shown in Table 4.

[0166] Table 4

[0167]

[0168] 6 Conclusion

[0169] Compared with the traditional method, the maximum interference of aerial fixed-point compensation (maneuver ④) is reduced by 93.26%, and the standard deviation is reduced by 83.46%. The improvement ratio is 604.52% of the traditional method.

Claims

1. A method for airborne fixed-point compensation of carrier interference based on magnetic tensor, characterized in that: include: Based on the mathematical mapping relationship between attitude change, the spatial position of the ferromagnetic body in the UAV carrier and the magnetic field interference, a carrier magnetic field interference model is established. The carrier magnetic field interference model is specifically as follows: ； Where, , is the vacuum permeability, is the distance between the i-th interference source and the k-th magnetometer, ( , , ) is the position coordinate of the k-th magnetometer, ( , , ) is the position coordinate of the i-th interference source, m is the number of interference sources, is the magnetic moment of the i-th interference source; the magnetic moment of the i-th interference source is specifically: ； Where, , is the magnetic susceptibility of the i-th interference source, 、 、 are the demagnetization coefficients of the i-th interference source in the l, t, and v directions, respectively. The l direction is along the direction of the machine arm, the t direction is perpendicular to the l direction, and the v direction is perpendicular to the plane enclosed by the l and t directions. is the volume of the ferromagnet, is the Euler rotation matrix, for They are all projections of the Earth's magnetic field on the carrier coordinate system at 0°. are the rotation angles of the UAV carrier around the three directions of l, t, and v, respectively. is the residual magnetization intensity of the i-th interference source; Based on the carrier magnetic field interference model, a carrier magnetic tensor contraction and merging interference compensation model is established, specifically: ； Where, is the interference of the carrier magnetic tensor contraction measured in the vector magnetometer array, is the compensation coefficient matrix; , n is the number of magnetometers in the vector magnetometer array, ， ， ， ； H ekx , H eky , H ekz They represent the projections of the background magnetic field at the k-th magnetometer position on the x, y, and z axes, respectively. , is the magnetic field measured by the k-th magnetometer, , is the carrier magnetic field interference model, The rotation matrix for converting the UAV carrier coordinate system to the sensor coordinate system, is the background magnetic field at the k-th magnetometer position, k=1,2,3…n, is the magnitude of the background magnetic field; The UAV performs a compensation maneuver at a fixed point in the air and obtains magnetic field data measured by each magnetometer in a vector magnetometer array installed on the UAV carrier; The magnetic field data measured by each magnetometer in the vector magnetometer array is combined with the scalar data of the Earth's magnetic field to calculate the projection of the background magnetic field at the position of the i-th magnetometer in the vector magnetometer array on the three axes; The projection of the background magnetic field on the three axes at the position of the i-th magnetometer in the vector magnetometer array is input into the carrier magnetic tensor contraction interference compensation model. At the same time, the optimization algorithm is used to calculate the compensation coefficient in the carrier magnetic tensor contraction interference compensation model to achieve magnetic compensation.

2. The method for airborne fixed-point compensation of carrier interference based on magnetic tensor according to claim 1, characterized in that: The UAV carrier is divided into m interference sources, and the magnetic field generated by the carrier at the kth magnetometer position in the vector magnetometer array is calculated as the carrier magnetic field interference model. The magnetic field generated by the carrier at the kth magnetometer position in the vector magnetometer array is the superposition of the magnetic fields of all interference sources on the carrier.

3. The method for airborne fixed-point compensation of carrier interference based on magnetic tensor according to claim 1, characterized in that: The objective function of the compensation coefficient of the carrier magnetic tensor contraction and merging interference compensation model calculated by the optimization algorithm is specifically: ； Where d represents the sampling point number, N is the total number of sampling points, and a is the compensation coefficient matrix. Constructed for the magnetic field data at the d-th sampling point Parameter matrix.

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