Multi-source error correction method for geomagnetic vector measurement based on the least squares two-step method

Abstract

The present invention provides a multi-source error correction method for geomagnetic vector measurement based on the least squares two-step method. First, a comprehensive compensation model for errors including three-axis fluxgate sensor error, misalignment error, soft magnetism and hard magnetism is established. Then, the measurement carrier is allowed to navigate and collect calibration data according to certain actions. The geomagnetic component constraint method is used to calculate various compensation parameters using the two-step least squares method. Finally, the measured data is compensated. The present invention can comprehensively compensate for the above-mentioned errors, does not require other auxiliary equipment, is simple to operate, has a fast calculation speed, and can be applied under actual mobile geomagnetic vector measurement conditions.

Description

Technical Field

[0001] The invention belongs to the technical field of geomagnetic vector measurement, and in particular relates to a geomagnetic vector measurement multi-source error correction method based on a least squares two-step method. Background Art

[0002] The geomagnetic field is a vector field inherent to the earth. The information obtained by measuring the geomagnetic vector field is richer, and it has incomparable advantages over geomagnetic scalar measurement. In the process of mobile geomagnetic vector measurement, the geomagnetic vector measurement system needs to be mounted on the measurement carrier (the carrier can be a measurement ship / boat, manned / unmanned aircraft, towed body, AUV, etc.). Usually, the geomagnetic vector measurement system includes a three-component magnetometer, a high-precision inertial navigation (attitude meter), a data acquisition module, a GNSS module, a data storage module, etc. During the movement of the carrier, the three-component magnetometer and the high-precision inertial navigation respectively measure the three-component magnetic field values ​​and attitude angle information at different points, and then rotate the three-component magnetic field according to the attitude angle information to obtain the geomagnetic vector in the geographic coordinate system.

[0003] At present, the instrument used for three-component magnetic measurement is mainly a three-axis fluxgate sensor. Due to the limitations of materials and processing technology, it has zero bias error, scale coefficient error, and three-axis non-orthogonality error, which will affect the measurement accuracy of the three-axis fluxgate sensor. Ideally, the coordinate system of the three-component magnetometer and the attitude meter are in an aligned state, and the three-component magnetic field can be accurately transformed to the geographic coordinate system; in actual engineering, the coordinate system of the three-component magnetometer and the attitude meter are not visible, and it is difficult to ensure the precise alignment of the two coordinate systems by simply relying on mechanical installation, that is, there is a misalignment error; the misalignment error will cause deviations in the three-component magnetic field attitude coordinate transformation, affecting the measurement accuracy of the vector magnetic field in the geographic coordinate system. The usual measurement carrier inevitably contains ferromagnetic materials in its power device, electrical equipment, and carrier structure, which will produce interference magnetic fields including hard magnetism, induced magnetic fields, and eddy current magnetic fields.

[0004] The steering error, misalignment error and carrier interference magnetic field of the above-mentioned three-axis fluxgate sensor will seriously affect the accuracy of geomagnetic vector measurement. Correcting and compensating these errors and interference magnetic fields are key technical issues in mobile geomagnetic vector measurement, and many scholars have carried out related research.

[0005] In the aspect of steering error correction of three-axis fluxgate sensor, Pang Xueliang et al. proposed a three-axis magnetic sensor error correction method based on genetic algorithm. First, the objective function is constructed, and the optimal solution of the objective function is obtained by genetic algorithm. Then, the measurement data is corrected. Numerical simulation shows that this method can converge stably and achieve high error parameter estimation accuracy (Pang Xueliang, Lin Chunsheng. Solution of three-axis magnetic sensor correction coefficient based on genetic algorithm [J]. Journal of Detection and Control, 2017, 39(1): 42-45, 51.). In terms of misalignment error correction, Pang Hongfeng et al. proposed a misalignment correction method for the geomagnetic vector system based on the axis winding method. The method requires that the three-axis magnetic sensor and the accelerometer be encapsulated in a non-magnetic regular hexahedron, and the non-magnetic regular hexahedron be placed on a non-magnetic turntable, and rotated around the X-axis and Z-axis of the non-magnetic regular hexahedron respectively, and the misalignment angles from the non-magnetic regular hexahedron to the three-axis magnetic sensor and the accelerometer are calculated respectively, and then the coordinate transformation relationship between the three-axis magnetic sensor and the accelerometer is determined (Pang Hongfeng, Zhang Qi, Wan Chengbiao et al. Geomagnetic vector system misalignment correction method based on the axis winding method, patent application number: 201410740758.9). In terms of carrier magnetic interference compensation, Liu Jihao et al. proposed a carrier magnetic interference vector compensation method. This method proposed an improved magnetic interference parameter determination criterion, but in the semi-physical simulation experiment, the component error after compensation was still as high as thousands of nT. It requires the three-axis magnetic sensor and the three-axis gyroscope to be installed on an aluminum plate, and it is assumed that the coordinate systems of the two are aligned, and then the measurement is completed under the conditions of no interference source and with interference source. It is not easy to achieve under actual carrier measurement conditions (Liu Jihao, Li Xihai, Zhang Ying, et al. A general method for carrier interference vector compensation in geomagnetic measurement [J]. Chinese Journal of Scientific Instrument, 2020, 41(11): 112-118.).

[0006] The above methods are all for correcting or compensating single measurement errors. In actual measurement, if the errors are corrected and compensated one by one, not only the procedure is complicated and the operability is low, but also the errors may be coupled, and the correction effect may be poor. In terms of comprehensive error correction, Zhang Qi et al. proposed a method for error correction of geomagnetic vector measurement system based on Lagrange multiplier method. This method uses a non-magnetic hexahedral box and a non-magnetic platform to establish linear equations including magnetic sensor error, misalignment error, soft magnetism and hard magnetism, and uses the total magnetic field constraint method to solve the error parameters and realize error correction (Zhang Qi, Wan Chengbiao, Pan Mengchun, Error correction method of geomagnetic vector measurement system based on Lagrange multiplier method, patent application number: CN201710067382.3). Li Ting et al. proposed a method for compensating the geomagnetic field measurement error based on damped particle swarm optimization. First, an error compensation model including magnetic sensor error and carrier magnetic interference was established. The model parameters were estimated using the damped particle swarm algorithm and the total field constraint method. Semi-physical experiments showed that a good compensation effect could be achieved for the total magnetic field error (Li Ting, Zhang Jinsheng, Wang Shicheng, et al. Geomagnetic field measurement error compensation based on damped particle swarm optimization [J]. Chinese Journal of Scientific Instrument, 2017, 38(10): 2446-2452).

[0007] In summary, there are still some problems in the existing error correction and compensation of geomagnetic vector measurement: 1) Correction and compensation are carried out for single errors, and comprehensive correction and compensation of multiple errors cannot be achieved, and the application efficiency and operability in practice are low; 2) The total magnetic field is used as a constraint condition for error parameter calculation, which has a good effect on the correction of total magnetic field errors, but a poor effect on the correction of geomagnetic vector errors; 3) The method has high limitations and requires complex equipment and tooling, which is difficult to apply under actual measurement conditions.

[0008] The above information disclosed in the background technology is only used to increase the understanding of the background technology of the present application, and therefore, it may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0009] In view of the above problems existing in the prior art, the present invention provides a multi-source error correction method for geomagnetic vector measurement based on the least squares two-step method.

[0010] In order to achieve the above technical objectives, the present invention adopts the following technical solutions: a multi-source error correction method for geomagnetic vector measurement based on the least squares two-step method, the method is:

[0011] S1. Establish measurement model:

[0012] B m =HB e +B0(Formula 2);

[0013] Among them, H=KC(I+M), B0=KCB h +b0, I is the identity matrix, B m =[B mx ,B my ,B mz ] T is the output value of the three-axis fluxgate sensor, B e =[B ex ,B ey ,B ez ] T is the projection vector of the geomagnetic field in the orthogonal magnetometer coordinate system, is the carrier induced magnetic field coefficient matrix, is the non-orthogonal error matrix of the three-axis fluxgate sensor, α, β, γ are non-orthogonal angles, is the scale factor matrix of the three-axis fluxgate sensor, B h =[B hx ,B hy ,B hz ] T is the projection of the carrier hard magnetism in the orthogonal magnetometer coordinate system, b0 = [b 0x ,b 0y ,b 0z ] T is the zero bias error vector of the three-axis fluxgate sensor;

[0014] S2. Obtain the error correction model based on the measurement model:

[0015]

[0016] in, is the geomagnetic projection vector in the inertial navigation coordinate system, is the rotation matrix from the orthogonal magnetometer coordinate system to the inertial navigation coordinate system, G is the coefficient matrix, B0 is the coefficient vector;

[0017] S3, collecting calibration data;

[0018] S4, using the IGRF model to calculate the background magnetic field and rotate it to the inertial navigation coordinate system;

[0019] The geomagnetic vector value in the geographic coordinate system calculated by the IGRF model is used to approximate the real background geomagnetic field value here; the magnetic field vector in the geographic coordinate system of the calibration area calculated by the IGRF model is assumed to be According to the attitude angle output by the attitude meter during the calibration process, By rotating the coordinates, we can get the magnetic field vector in the inertial navigation coordinate system:

[0020] in, represents the geomagnetic vector in the inertial navigation coordinate system, Represents the transformation matrix from geographic coordinate system to inertial navigation coordinate system,

[0021] r, p, and h represent the roll angle, pitch angle, and heading angle output by the attitude instrument, respectively;

[0022] S5. Adopt the geomagnetic component constraint method and use the least square method to obtain the coefficient matrix G′, and then obtain the matrix G:

[0023] make have

[0024] Among them, the coefficient matrix G is a 3×3 matrix, and the vector B0 is a 3×1 matrix. get:

[0025] in,

[0026] Due to the collection of multiple sets of calibration data: B m (i) (i=1,2,…,n,n≥12), (Formula 8) can be written as:

[0027] in, According to the principle of least squares, the best estimate of G′ is obtained using (Formula 9);

[0028] Obtain the coefficient matrix G;

[0029] S6. According to the least squares principle, vector B0 is obtained:

[0030] Let G4 = [g 14 ,g 24 ,g 34 ] T , which is a known quantity, according to (Formula 8), we get GB0=G4 (Formula 11);

[0031] Obtain an estimated value of B0 based on the principle of least squares;

[0032] S7. Calculate the geomagnetic vector in the inertial navigation coordinate system according to (Formula 5)

[0033] S8. Rotate the geomagnetic vector in the inertial navigation coordinate system to the geographic coordinate system:

[0034] According to the attitude angle output by the attitude instrument Rotate the coordinates to get the geomagnetic vector in the geographic coordinate system

[0035] in, is the rotation matrix from the inertial navigation coordinate system to the geographic coordinate system:

[0036]

[0037] As described above, in the multi-source error correction method for geomagnetic vector measurement based on the least squares two-step method, after the geomagnetic vector measurement system is installed on the mobile carrier, the carrier coordinate system is consistent with the attitude instrument coordinate system.

[0038] The multi-source error correction method for geomagnetic vector measurement based on the least squares two-step method as described above establishes an error correction model including three-axis fluxgate sensor error, misalignment error, soft magnetic and hard magnetic interference.

[0039] As described above, in the multi-source error correction method for geomagnetic vector measurement based on the least squares two-step method, the method for collecting calibration data is as follows: an open area is selected near the survey area where the geomagnetic gradient is lower than a set value and the surrounding magnetic interference is less than a set value, and a point close to the center of the area is selected. With this point as the center, the carrier is commanded to perform maneuvering navigation to collect calibration data.

[0040] As described above, the multi-source error correction method for geomagnetic vector measurement based on the least squares two-step method, the maneuvering mode is: with the selected point as the center, the carrier is ordered to navigate around the point clockwise and counterclockwise at the measured speed and minimum turning radius, and rotate one circle each time.

[0041] As described above, the multi-source error correction method for geomagnetic vector measurement based on the least squares two-step method, the maneuvering mode is: with the selected point as the center, the carrier makes a "cross" round-trip navigation.

[0042] As described above, in the multi-source error correction method for geomagnetic vector measurement based on the least squares two-step method, the length of each side of the "cross" is 20 times the length of the carrier.

[0043] Compared with the prior art, the advantages and positive effects of the present invention are as follows: the present invention is based on the multi-source error correction method of geomagnetic vector measurement based on the least squares two-step method, firstly, a comprehensive error compensation model including three-axis fluxgate sensor error, misalignment error, soft magnetism and hard magnetism is established, then the measurement carrier is allowed to navigate and collect calibration data according to certain actions, and the geomagnetic component constraint method is adopted, and the two-step least squares calculation is used to calculate various compensation parameters, and finally the measured data is compensated. The present invention can comprehensively compensate for the above-mentioned errors, does not require other auxiliary equipment, is simple to operate, has a fast calculation speed, and can be applied under actual mobile geomagnetic vector measurement conditions. The present invention can realize rapid correction and compensation for three-component magnetometer errors, misalignment errors, and carrier magnetic field interference in geomagnetic vector measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0045] Figure 1 Schematic diagram of the coordinate system of the geomagnetic vector measurement system.

[0046] Figure 2 This is the relationship diagram of the magnetometer coordinate system.

[0047] Figure 3 Schematic diagram of carrier maneuverability.

[0048] Figure 4 This is a flow chart of the multi-source error correction method for geomagnetic vector measurement based on the least squares two-step method. DETAILED DESCRIPTION

[0049] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0050] It should be noted that in the description of the present invention, the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer" and the like indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings, which are only for the convenience of description, and do not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0051] To make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0052] The geomagnetic vector measurement system has the following coordinate systems: inertial navigation coordinate system OX p Y p Z p , ideal orthogonal magnetometer coordinate system OX m Y m Z m , both of which are orthogonal coordinate systems, and their schematic diagrams are as follows Figure 1 ; In addition, the actual magnetometer coordinate system OX′ is composed of the three sensitive axes of the three-axis fluxgate sensorm Y m 'Z' m , due to the non-orthogonal error of the three-axis fluxgate sensor, the actual magnetometer coordinate system is a non-orthogonal coordinate system. Its corresponding relationship with the ideal orthogonal magnetometer coordinate system is as follows: Figure 2 After the geomagnetic vector measurement system is installed on the mobile carrier, the carrier coordinate system is assumed to be consistent with the inertial navigation coordinate system.

[0053] like Figure 4 As shown, the method of this embodiment includes the following steps:

[0054] S1. Establish measurement model:

[0055] Under the above coordinate system relationship, when only the three-axis fluxgate sensor error, soft magnetic and hard magnetic interference are considered, the measurement model under the mobile geomagnetic vector measurement conditions can be established:

[0056] B m =KC(B e +MB e +B h )+b0 (Formula 1);

[0057] Among them, B m =[B mx ,B my ,B mz ] T is the output value of the three-axis fluxgate sensor, B e =[B ex ,B ey ,B ez ] T is the projection vector of the geomagnetic field in the orthogonal magnetometer coordinate system, is the carrier induced magnetic field coefficient matrix, is the non-orthogonal error matrix of the three-axis fluxgate sensor (α, β, γ are non-orthogonal angles, such as Figure 2 ), is the scale factor matrix of the three-axis fluxgate sensor, B h =[B hx ,B hy ,B hz ] T is the projection of the carrier hard magnetism in the orthogonal magnetometer coordinate system, b0 = [b 0x ,b 0y ,b 0z ] T is the zero bias error vector of the three-axis fluxgate sensor.

[0058] Simplifying (Formula 1) yields: B m =HB e +B0 (Formula 2);

[0059] Among them, H=KC(I+M), B0=KCB h +b0.

[0060] S2. Obtain the error correction model based on the measurement model:

[0061] Transform (Formula 2) to obtain the error correction model: e =H -1 (B m -B0) (Formula 3);

[0062] Among them, B e is the projection vector of the geomagnetic field in the orthogonal magnetometer coordinate system. In fact, there is a misalignment error between the orthogonal magnetometer coordinate system and the inertial navigation coordinate system. In order to use the attitude angle and heading angle output by the high-precision inertial navigation (attitude meter) to convert B e To rotate to the geographic coordinate system, the orthogonal magnetometer coordinate system and the inertial navigation coordinate system should be aligned first, that is, first B e Rotate to the inertial coordinate system:

[0063] in, is the geomagnetic vector rotated from the geomagnetic field to the inertial navigation coordinate system, is the rotation matrix from the orthogonal magnetometer coordinate system to the inertial navigation coordinate system.

[0064] make Then we have:

[0065] According to (Formula 5), ​​if the coefficient matrix G and the coefficient vector B0 are obtained, the true value of the geomagnetic vector in the inertial navigation coordinate system can be obtained through the output value of the three-axis fluxgate sensor.

[0066] In actual mobile geomagnetic vector measurement, before or after the measurement task begins, the carrier needs to navigate according to certain actions, and the measurement system is turned on to collect calibration data for the calculation of error correction parameters.

[0067] S3. Select the calibration area and collect calibration data B m (i) and attitude angle A (r,p,h) (i), (i=1,2,...,n,n≥12);.

[0068] In actual operation, an open area with a small geomagnetic gradient (geomagnetic gradient is less than the set value) and no obvious magnetic interference source (magnetic interference is less than the set value) is selected near the survey area. A point close to the center of the area is selected. With this point as the center, the carrier is ordered to perform maneuvering navigation to collect calibration data. The maneuvering method is: 1) With the selected point as the center, the carrier is ordered to navigate clockwise and counterclockwise around the point at the measured speed and minimum turning radius, and rotate one circle each time; 2) With the selected point as the center, the carrier is ordered to make a "cross" round-trip navigation. The length of each side of the "cross" is defined according to the length of the carrier, and generally 20 times the length of the carrier is selected. Figure 1 "L" represents the length of the carrier. The schematic diagram of the carrier maneuvering trajectory is as follows Figure 3 .

[0069] S4. Use the IGRF model to calculate the background magnetic field and rotate it to the inertial navigation coordinate system.

[0070] Since the geomagnetic gradient in the calibration area is small and there is no obvious magnetic interference source around, the geomagnetic vector value in the geographic coordinate system calculated by the IGRF model can be used to approximate the real background geomagnetic field value here; the magnetic field vector in the geographic coordinate system of the calibration area calculated by the IGRF model is assumed to be According to the attitude angle output by the high-precision inertial navigation during the calibration process, By rotating the coordinates, the magnetic field vector in the inertial navigation coordinate system can be obtained. The process is as follows:

[0071]

[0072] in, Represents the geomagnetic vector of the background magnetic field transferred to the inertial navigation coordinate system, The transformation matrix from geographic coordinate system to inertial navigation coordinate system is:

[0073] r, p, and h represent the roll angle, pitch angle, and heading angle output by the high-precision inertial navigation system, respectively.

[0074] S5. Adopt the geomagnetic component constraint method and use the least square method to obtain the coefficient matrix G′, and then obtain the matrix G:

[0075] Combine (Formula 5) and (Formula 6), if there is This means that the coefficient matrix G and vector B0 are correct; however, in practice, both magnetic sensors and high-precision inertial navigation systems have measurement noise. and will not be completely equal, so have:

[0076]

[0077] The coefficient matrix G is a 3×3 matrix, and the vector B0 is a 3×1 matrix. Expand it and we get:

[0078]

[0079] in,

[0080] In the actual calibration process, multiple sets of calibration data will be collected, including: B m (i) (i=1,2,...,n,n≥12).

[0081] (Formula 8) can be rewritten as:

[0082] in, According to the principle of least squares method, the best estimate of G′ can be obtained using (Formula 9), that is,

[0083]

[0084] After obtaining G′, the coefficient matrix G is obtained.

[0085] S6. According to the least squares principle, vector B0 is obtained:

[0086] Let G4 = [g 14 ,g 24 ,g 34 ] T , which is a known quantity, according to (Formula 8), we have: GB0 = G4 (Formula 11)

[0087] Similarly, according to the principle of least squares, the estimated value of B0 can be obtained, that is,

[0088] B0=(G T G) -1 G T G4 (Formula 12).

[0089] S7. Calculate the geomagnetic vector in the inertial navigation coordinate system according to (Formula 5) The measured data is corrected according to (Formula 5).

[0090] Through the above derivation and calculation, the coefficient matrix G and vector B0 have been obtained. The geomagnetic vector data B obtained in the actual measurement operation can be obtained according to (Formula 5). m Perform real-time online compensation or offline compensation to obtain the geomagnetic vector in the inertial navigation coordinate system

[0091] S8. Rotate the geomagnetic vector in the inertial navigation coordinate system to the geographic coordinate system:

[0092] According to the attitude angle output by high-precision inertial navigation By rotating the coordinates, we can get the geomagnetic vector B in the geographic coordinate system. g =[B gx ,B gy ,B gz ] T , the process is as follows:

[0093]

[0094] in, is the rotation matrix from the inertial navigation coordinate system to the geographic coordinate system:

[0095] r, p, and h represent the roll angle, pitch angle, and heading angle output by the high-precision inertial navigation system, respectively.

[0096] This embodiment sorts out the correspondence between various coordinate systems, and establishes an error correction model that includes three-axis fluxgate sensor error, misalignment error, soft magnetic and hard magnetic interference based on the inertial navigation coordinate system. This embodiment can correct and compensate for multiple errors and interferences at one time, which is more operational and more efficient than correcting single errors separately.

[0097] During the calibration data collection process, this embodiment allows the carrier to navigate clockwise and counterclockwise around "O" and to navigate back and forth around "X" respectively; compared with the traditional "eight" orientation method, it saves more time and can reduce the influence of daily geomagnetic changes in the compensation process; compared with the method of circling "O" alone, it can better cover the possible postures that may occur in the measurement, and the collected calibration data is more effective.

[0098] This embodiment adopts the geomagnetic component constraint method in solving the error parameters, and the solved error parameters have higher accuracy in compensating component errors. Compared with the geomagnetic total field constraint, the calculated compensation parameters are more accurate and have better compensation effect on geomagnetic vector data.

[0099] This embodiment adopts a two-step least squares algorithm to solve the correction matrix G and the vector B0 respectively. This embodiment adopts the least squares method to calculate the compensation parameters. Compared with general iterative calculation methods, Kalman filtering and other methods, this method has faster calculation speed and higher efficiency.

[0100] This embodiment does not require auxiliary equipment, has a simple implementation process, and is highly practical.

[0101] This embodiment has strong versatility and can be applied to comprehensive compensation of multi-source errors in mobile geomagnetic vector measurement under carrier conditions such as measurement ships / boats, manned / unmanned aircraft, towed bodies, and AUVs.

[0102] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for a person skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to replace some of the technical features therein by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions claimed to be protected by the present invention.

Claims

1. A method for multi-source error correction of geomagnetic vector measurement based on the least squares two-step method, characterized in that: The method is: S1. Establish measurement model: B m =HB e +B0(Formula 2); Among them, H=KC(I+M), B0=KCB h +b0, I is the identity matrix, B m =[B mx ,B my ,B mz ] T is the output value of the three-axis fluxgate sensor, B e =[B ex ,B ey ,B ez ] T is the projection vector of the geomagnetic field in the orthogonal magnetometer coordinate system, is the carrier induced magnetic field coefficient matrix, is the non-orthogonal error matrix of the three-axis fluxgate sensor, α, β, γ are non-orthogonal angles, is the scale factor matrix of the three-axis fluxgate sensor, B h =[B hx ,B hy ,B hz ] T is the projection of the carrier hard magnetism in the orthogonal magnetometer coordinate system, b0 = [b 0x ,b 0y ,b 0z ] T is the zero bias error vector of the three-axis fluxgate sensor; S2. Obtain the error correction model based on the measurement model: in, is the geomagnetic projection vector in the inertial navigation coordinate system, is the rotation matrix from the orthogonal magnetometer coordinate system to the inertial navigation coordinate system, G is the coefficient matrix, B0 is the coefficient vector; S3, collecting calibration data; S4, using the IGRF model to calculate the background magnetic field and rotate it to the inertial navigation coordinate system; The geomagnetic vector value in the geographic coordinate system calculated by the IGRF model is used to approximate the real background geomagnetic field value here; the magnetic field vector in the geographic coordinate system of the calibration area calculated by the IGRF model is assumed to be According to the attitude angle output by the attitude meter during the calibration process, By rotating the coordinates, we can get the magnetic field vector in the inertial navigation coordinate system: in, represents the geomagnetic vector in the inertial navigation coordinate system, Represents the transformation matrix from geographic coordinate system to inertial navigation coordinate system, r, p, and h represent the roll angle, pitch angle, and heading angle output by the attitude instrument, respectively; S5. Adopt the geomagnetic component constraint method and use the least square method to obtain the coefficient matrix G′, and then obtain the coefficient matrix G: make have Among them, the coefficient matrix G is a 3×3 matrix, and the vector B0 is a 3×1 matrix. get: in, Due to the collection of multiple sets of calibration data: B m (i) (i=1,2,…,n,n≥12), Formula 8 can be written as: in, According to the principle of least squares method, the best estimate of G′ is obtained using formula 9; Obtain the coefficient matrix G; S6. According to the least squares principle, vector B0 is obtained: Let G4 = [g 14 ,g 24 ,g 34 ] T , which is a known quantity, according to formula 8, GB0=G4 (formula 11); Obtain an estimated value of B0 based on the principle of least squares; S7. Calculate the geomagnetic vector in the inertial navigation coordinate system according to formula 5 S8. Rotate the geomagnetic vector in the inertial navigation coordinate system to the geographic coordinate system: According to the attitude angle output by the attitude instrument Rotate the coordinates to obtain the geomagnetic vector B in the geographic coordinate system g =[B gx ,B gy ,B gz ] T , in, is the rotation matrix from the inertial navigation coordinate system to the geographic coordinate system:

2. The multi-source error correction method for geomagnetic vector measurement based on the least squares two-step method according to claim 1 is characterized in that: After the geomagnetic vector measurement system is installed on the mobile carrier, the carrier coordinate system is consistent with the attitude instrument coordinate system.

3. The multi-source error correction method for geomagnetic vector measurement based on the least squares two-step method according to claim 1 is characterized in that: The method establishes a multi-source error correction model including three-axis fluxgate sensor error, misalignment error, soft magnetic and hard magnetic interference.

4. The multi-source error correction method for geomagnetic vector measurement based on the least squares two-step method according to claim 1 is characterized in that: The method for collecting calibration data is as follows: select an open area near the survey area where the geomagnetic gradient is lower than the set value and the surrounding magnetic interference is less than the set value, select a point close to the center of the area, and use this point as the center to make the carrier perform maneuvering navigation to collect calibration data.

5. The method for multi-source error correction of geomagnetic vector measurement based on the least squares two-step method according to claim 4 is characterized in that: The maneuvering method is: with the selected point as the center, the carrier is ordered to navigate around the point clockwise and counterclockwise at the measured speed and minimum turning radius, and rotate one circle each time.

6. The multi-source error correction method for geomagnetic vector measurement based on the least squares two-step method according to claim 4 is characterized in that: The maneuvering method is: with the selected point as the center, the carrier makes a "cross" reciprocating navigation.

7. The method for multi-source error correction of geomagnetic vector measurement based on the least squares two-step method according to claim 6 is characterized in that: The length of each side of the "cross" is 20 times the length of the carrier.

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