CN107894241A - A kind of unmanned plane magnetic sensor calibration method, unmanned plane based on ellipsoid fitting - Google Patents
A kind of unmanned plane magnetic sensor calibration method, unmanned plane based on ellipsoid fitting Download PDFInfo
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- CN107894241A CN107894241A CN201711289238.0A CN201711289238A CN107894241A CN 107894241 A CN107894241 A CN 107894241A CN 201711289238 A CN201711289238 A CN 201711289238A CN 107894241 A CN107894241 A CN 107894241A
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Abstract
The invention belongs to unmanned air vehicle technique field, disclose a kind of unmanned plane magnetic sensor calibration method, unmanned plane based on ellipsoid fitting, unmanned plane is divided into six postures, be respectively X-axis straight up and straight down, Y-axis straight up and straight down, Z axis straight up and straight down；Unmanned plane is rotated on each posture position, collects a series of output valve of Magnetic Sensor under different postures；Ellipsoidal Surface is fitted by obtained Magnetic Sensor output valve；Calibration factor is obtained by obtained Ellipsoidal Surface；Compensated using the output of calibration parameter and calibrating patterns to unmanned plane magnetic sensor.The present invention is independent of external device, simple to operate, calibration accuracy is high, can flexibly use in all case, can 6 coefficients such as calibrated scale coefficient and null offset, improve the measurement accuracy of Magnetic Sensor.
Description
Technical field
The invention belongs to unmanned air vehicle technique field, more particularly to a kind of unmanned plane magnetic sensor calibration based on ellipsoid fitting
Method, unmanned plane.
Background technology
Magnetic Sensor determines unmanned plane course angle by measuring magnetic field of the earth, and it can provide nothing for flight control system
Man-machine course, then the attitude information of unmanned plane can be obtained by the measurement data of Magnetic Sensor, so that unmanned plane can
Carry out navigational guidance and control.But Magnetic Sensor is producing and can produce certain error unavoidably in installation process, in addition, by
Weaker in earth magnetic field intensity, Magnetic Sensor is highly susceptible to the influence of external environment, so in order to obtain high-precision measurement
Information, need to calibrate Magnetic Sensor before the use.Existing Magnetic Sensor calibration method mainly has data fusion method
And given benchmark method, data fusion method refers to carry out data fusion using GPS metrical informations and Inertial Measurement Unit, then to magnetic
The measurement data of sensor is filtered calibration；Unmanned plane is needed to provide GPS information, for the unmanned plane to fly indoors
For, because GPS sensor does not receive gps signal, it is impossible to be used in the Magnetic Sensor calibration of indoor unmanned plane.Given benchmark method
Refer to using the posture of measuring apparatus magnetic compass in all directions such as turntables, can be accurate when magnetic field environment change is little
Calibrate Magnetic Sensor.But this method needs by means of outside large scale equipment, to be only applicable to the occasion of turntable.Turn for no
The occasion of platform can not then use the Magnetic Sensor of this method calibration unmanned plane.
In summary, the problem of prior art is present be：The GPS sensor of the unmanned plane of indoor flight does not receive GPS
Signal, it is impossible to be used in the Magnetic Sensor calibration of indoor unmanned plane；Given benchmark method needs to use turntable, can only be in the field for having turntable
Close and use, applicability has considerable restraint, it is impossible to be used in the Magnetic Sensor calibration of the unmanned plane without turntable.
The content of the invention
The problem of existing for prior art, the invention provides a kind of unmanned plane magnetic sensor school based on ellipsoid fitting
Quasi- method, unmanned plane.
The present invention is achieved in that a kind of unmanned plane magnetic sensor calibration method based on ellipsoid fitting, described to be based on
The unmanned plane magnetic sensor calibration method of ellipsoid fitting comprises the following steps：
Step 1, unmanned plane is divided into six postures, be respectively X-axis straight up and straight down, Y-axis straight up and
Straight down, Z axis is straight up and straight down；
Step 2, unmanned plane is rotated on each posture position, collect a series of Magnetic Sensor under different postures
Output valve；
Step 3, because Magnetic Sensor output valve is integer, so needing to carry out data conversion to output valve, it is converted into reality
The Magnetic Sensor measured value on border, then according to least square fitting Ellipsoidal Surface, the Ellipsoidal Surface fitted includes ellipsoid
The calibration factor of sphere center position and each axle；
Step 4, calibration is obtained by the sphere center position of the ellipsoid fitted and the calibration factor and calibrating patterns of each axle
Coefficient, including three null offsets and three calibration factors；
Step 5, entered using the output of six calibration factors and calibrating patterns to each reference axis of unmanned plane accelerometer
Row compensation, obtains the real measured value of accelerometer.
Further, the calibrating patterns of the unmanned plane magnetic sensor calibration method Magnetic Sensor based on ellipsoid fitting are：
Hr=K (Hm-H0)；
Deploy：
Wherein Hmx、Hmy、HmzFor the measured value of three axles of Magnetic Sensor, Hrx、Hry、HrzFor the true of three axles of Magnetic Sensor
Value, H0x、Hoy、H0zFor the zero drift error of three axles of Magnetic Sensor, kx、ky、kzFor the calibration factor of three axles of Magnetic Sensor.
Further, when the static placement of unmanned plane, relation between three output valves of the Magnetic Sensor after correction：
Wherein, const represents local earth magnetic field intensity, then is obtained by calibrating patterns：
Further, the quadric general equation of ellipsoid is：
F (ξ, z)=ξTZ=ax2+by2+cz2+ 2dxy+2exz+2fyz+2px+2qy+2rz+t=0；
Wherein ξ=[a, b, c, d, e, f, p, q, r, t]TFor quadratic surface parameter vector to be asked, v=[x2,y2,z2,2xy,
2xz,2yz,2x,2y,2z,1]TFor the computing mix vector of measurement data；F (ξ, v) is that measurement data (x, y, z) arrives secondary song
Face F (ξ, z) algebraic distance；During Quadratic Surface Fitting, the quadratic sum for choosing measurement data to quadratic surface algebraic distance is minimum
For judgment criterion：
Wherein：
The constraints that ellipsoid fitting algorithm based on least square method obtains Ellipsoidal Surface is：
F (ξ, v) matrix of the Quadratic Function Optimization for the best fit Ellipsoidal Surface that least square method with Ellipsoidal Restrictions obtains
It is expressed as vector form：
(X-X0)TA(X-X0)=1；
Wherein,It is the matrix relevant with the axial length of ellipsoid three and half and the ellipsoid anglec of rotation,It is then the center point coordinate of fitting ellipsoid.
Further, obtained according to the measurement calibrating patterns of Magnetic Sensor：
(Hr)T(Hr)=[K (Hm-H0)]T[K(Hm-H0)]=| | const | |2；
Arrange：
Contrast ellipsoid fitting formula obtains：
Ellipsoid is fitted, goes out calibration factor using the parametric solution of ellipsoid.
Another object of the present invention is to provide the unmanned plane magnetic sensor calibration based on ellipsoid fitting described in a kind of utilization
The unmanned plane of method.
Advantages of the present invention and good effect are：Independent of the large-scale external device as three-axle table, also it is not required to
Extraneous the positional informations such as GPS are provided, the occasion such as outdoor can be used flexibly indoors, it is only necessary to place unmanned plane sensor
Rotation process is carried out under six posture positions, Ellipsoidal Surface is then gone out with regard to that can obtain calibration factor by least square fitting
With 6 coefficients of null offset.Compared with calibrating Magnetic Sensor using turntable, this method need not fix unmanned plane magnetic sensing
Device, operation is obvious simple, and prover time significantly shortens.Test result indicates that this method can improve the survey of unmanned plane sensor
Accuracy of measurement 4%, there is certain engineering application to be worth.
Brief description of the drawings
Fig. 1 is the unmanned plane magnetic sensor calibration method flow chart provided in an embodiment of the present invention based on ellipsoid fitting.
Fig. 2 is experimental result schematic diagram provided in an embodiment of the present invention.
Fig. 3 is experimental result schematic diagram provided in an embodiment of the present invention.
Embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, with reference to embodiments, to the present invention
It is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not used to
Limit the present invention.
The present invention is simple to operate, independent of external device, suitable for the quick school of unmanned plane magnetic sensor of most occasions
It is accurate.
The application principle of the present invention is explained in detail below in conjunction with the accompanying drawings.
As shown in figure 1, the unmanned plane magnetic sensor calibration method provided in an embodiment of the present invention based on ellipsoid fitting includes
Following steps：
S101：Unmanned plane is divided into six postures, be respectively X-axis straight up and straight down, Y-axis it is straight up and perpendicular
It is straight downwards, Z axis straight up and straight down；
S102：Unmanned plane is rotated on each posture position, collects a series of Magnetic Sensor under different postures
Output valve；
S103：Ellipsoidal Surface is fitted by the Magnetic Sensor output valve measured；
S104：Calibration factor is obtained by the Ellipsoidal Surface fitted；
S105：Compensated using the output of calibration parameter and calibrating patterns to unmanned plane magnetic sensor.
In a preferred embodiment of the invention：The calibrating patterns of Magnetic Sensor are：
Hr=K (Hm-H0)；
Expansion can obtain：
Wherein Hmx、Hmy、HmzFor the measured value of three axles of Magnetic Sensor, Hrx、Hry、HrzFor the true of three axles of Magnetic Sensor
Value, H0x、Hoy、H0zFor the zero drift error of three axles of Magnetic Sensor, kx、ky、kzFor the calibration factor of three axles of Magnetic Sensor.
The calibration of Magnetic Sensor is exactly that the calibration factor of three above zero drift error and three axles is obtained by certain method.
When the static placement of unmanned plane, there is following relation between three output valves of the Magnetic Sensor after correction：
Wherein, const represents local earth magnetic field intensity, then can be obtained by calibrating patterns：
From the foregoing, it will be observed that when if the calibration factor of three axles of Magnetic Sensor is incomplete same, during the measurement of Magnetic Sensor
It will be distributed on an ellipsoid.So the present invention is exactly to fit an ellipsoid, Ran Hougen by measuring multi-group data
The calibration factor of Magnetic Sensor is solved according to the ellipsoid fitted, so this calibration method is called ellipsoid fitting.
Ellipsoid is special quadratic surface, and quadric general equation is：
F (ξ, z)=ξTZ=ax2+by2+cz2+ 2dxy+2exz+2fyz+2px+2qy+2rz+t=0；
Wherein ξ=[a, b, c, d, e, f, p, q, r, t]TFor quadratic surface parameter vector to be asked, v=[x2,y2,z2,2xy,
2xz,2yz,2x,2y,2z,1]TFor the computing mix vector of measurement data.F (ξ, v) is that measurement data (x, y, z) arrives secondary song
Face F (ξ, z) algebraic distance.During Quadratic Surface Fitting, the quadratic sum for choosing measurement data to quadratic surface algebraic distance is minimum
For judgment criterion, i.e.,：
Wherein：
The basic principle of ellipsoid fitting is exactly to make the quadratic sum of measurement data to the distance of ellipsoidal surfaces minimum, but can not
The combination of each data is ensured on the curved surface of ellipsoid, therefore it is ellipse to introduce the ellipsoid fitting algorithm acquisition based on least square method
The constraints of ball curved surface is：
F (ξ, v) matrix of the Quadratic Function Optimization for the best fit Ellipsoidal Surface that least square method with Ellipsoidal Restrictions obtains
Expression can be arranged as vector form：
(X-X0)TA(X-X0)=1；
Wherein,It is the matrix relevant with the axial length of ellipsoid three and half and the ellipsoid anglec of rotation,It is then the center point coordinate of fitting ellipsoid.
It can be obtained according to the measurement calibrating patterns of Magnetic Sensor：
(Hr)T(Hr)=[K (Hm-H0)]T[K(Hm-H0)]=| | const | |2；
Arrangement can obtain：
Contrast ellipsoid fitting formula can obtain：
As long as from the foregoing, it will be observed that fitting ellipsoid, can just the parametric solution of ellipsoid be utilized to go out calibration factor.
The application effect of the present invention is explained in detail with reference to experiment.
Unmanned plane magnetic sensor is calibrated by Magnetic Sensor calibration steps set forth above.Unmanned plane is placed on
Save under the six kinds of postures proposed, then rotate horizontally aircraft, gathered data respectively under each posture.
As shown in Figure 2, the measured value APPROXIMATE DISTRIBUTION of unmanned plane magnetic sensor is on an ellipsoid.Then according to upper section institute
Show step calibration null offset and calibration factor.By the Magnetic Sensor calibration steps of proposition of the invention to unmanned plane magnetic sensor
Calibrated.After the completion of calibration, in order to verify the validity of the bearing calibration, Magnetic Sensor is fixed on accurate course
On turntable, make three reference axis of Magnetic Sensor consistent with the sensing of the axle of turntable three.Then sensor is started, respectively collection sensing
It is as shown in Figure 3 with the output valve after calibration, experimental result before the calibration of device.After the completion of calibration, keep gained and obtain null offset
And calibration factor.Then Magnetic Sensor is fixed on the turntable with accurate course, makes the sensing one of Magnetic Sensor and turntable
Cause.Then sensor is started, it is as shown in Figure 3 with the output valve after calibration, experimental result before the calibration of collection sensor respectively.
Ideally, the course angle error amount after calibration should be 0.Due to noise be present under actual conditions,
Actual measured value may have slight error.From the figure 3, it may be seen that about there is about 0.6 degree of course angle mistake for Magnetic Sensor before calibration
Difference, course angle error is reduced to about 0.15 degree after calibration.So the calibration method significantly reduces the error of Magnetic Sensor, carry
High measurement accuracy.
Unmanned plane magnetic sensor calibration method provided by the invention based on ellipsoid fitting can be calibrated quickly and accurately
The null offset of Magnetic Sensor and calibration factor；Without relying on large-scale precision equipment, unmanned plane need to only be revolved in different postures
Circle.In addition, amount of calculation is small, arithmetic speed is fast, can be rapidly completed demarcation, has certain engineering application value.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention
All any modification, equivalent and improvement made within refreshing and principle etc., should be included in the scope of the protection.
Claims (6)
1. a kind of unmanned plane magnetic sensor calibration method based on ellipsoid fitting, it is characterised in that described based on ellipsoid fitting
Unmanned plane magnetic sensor calibration method comprises the following steps：
Step 1, unmanned plane is divided into six postures, be respectively X-axis straight up and straight down, Y-axis straight up and vertically
Downwards, Z axis is straight up and straight down；
Step 2, unmanned plane is rotated on each posture position, collect a series of the defeated of Magnetic Sensor under different postures
Go out value；
Step 3, data conversion is carried out to output valve, actual Magnetic Sensor measured value is converted into, according to least square fitting
Ellipsoidal Surface, the Ellipsoidal Surface fitted include the sphere center position of ellipsoid and the calibration factor of each axle；
Step 4, calibration system is obtained by the sphere center position of the ellipsoid fitted and the calibration factor and calibrating patterns of each axle
Number, including three null offsets and three calibration factors；
Step 5, mended using the output of six calibration factors and calibrating patterns to each reference axis of unmanned plane accelerometer
Repay, obtain the real measured value of accelerometer.
2. the unmanned plane magnetic sensor calibration method based on ellipsoid fitting as claimed in claim 1, it is characterised in that the base
It is in the calibrating patterns of the unmanned plane magnetic sensor calibration method Magnetic Sensor of ellipsoid fitting：
Hr=K (Hm-H0)；
Deploy：
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H0x、Hoy、H0zFor the zero drift error of three axles of Magnetic Sensor, kx、ky、kzFor the calibration factor of three axles of Magnetic Sensor.
3. the unmanned plane magnetic sensor calibration method based on ellipsoid fitting as claimed in claim 2, it is characterised in that when nobody
During the static placement of machine, relation between three output valves of the Magnetic Sensor after correction：
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Wherein, const represents local earth magnetic field intensity, then is obtained by calibrating patterns：
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4. the unmanned plane magnetic sensor calibration method based on ellipsoid fitting as claimed in claim 1, it is characterised in that ellipsoid two
The general equation of secondary curved surface is：
F (ξ, z)=ξTZ=ax2+by2+cz2+ 2dxy+2exz+2fyz+2px+2qy+2rz+t=0；
Wherein ξ=[a, b, c, d, e, f, p, q, r, t]TFor quadratic surface parameter vector to be asked, v=[x2,y2,z2,2xy,2xz,
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The algebraic distance of (ξ, z)；During Quadratic Surface Fitting, the quadratic sum of selection measurement data to quadratic surface algebraic distance is minimum to be sentenced
Disconnected criterion：
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The constraints that ellipsoid fitting algorithm based on least square method obtains Ellipsoidal Surface is：
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F (ξ, v) matrix of the Quadratic Function Optimization for the best fit Ellipsoidal Surface that least square method with Ellipsoidal Restrictions obtains represents
For vector form：
(X-X0)TA(X-X0)=1；
Wherein,It is the matrix relevant with the axial length of ellipsoid three and half and the ellipsoid anglec of rotation,
It is then the center point coordinate of fitting ellipsoid.
5. the unmanned plane magnetic sensor calibration method based on ellipsoid fitting as claimed in claim 4, it is characterised in that according to magnetic
The measurement calibrating patterns of sensor obtain：
(Hr)T(Hr)=[K (Hm-H0)]T[K(Hm-H0)]=| | const | |2；
Arrange：
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Contrast ellipsoid fitting formula obtains：
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Ellipsoid is fitted, goes out calibration factor using the parametric solution of ellipsoid.
6. a kind of utilize the unmanned plane magnetic sensor calibration method based on ellipsoid fitting described in any one of Claims 1 to 55
Unmanned plane.
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Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108761548A (en) * | 2018-05-25 | 2018-11-06 | 哈尔滨工程大学 | The miniature magnetometers magnetic disturbance backoff algorithm of constraint least square ellipsoid fitting |
| CN109059960A (en) * | 2018-07-18 | 2018-12-21 | 福州大学 | A kind of calibration method of three-dimensional electronic compass |
| CN109238262A (en) * | 2018-11-05 | 2019-01-18 | 珠海全志科技股份有限公司 | A kind of course attitude algorithm and compass calibrate anti-interference method |
| CN109781144A (en) * | 2019-01-30 | 2019-05-21 | 京东方科技集团股份有限公司 | Data correcting method, device, electronic equipment and computer readable storage medium |
| CN110398702A (en) * | 2019-06-19 | 2019-11-01 | 北京摩高科技有限公司 | A kind of real-time online magnetic calibration method based on Multi-sensor Fusion |
| CN110514228A (en) * | 2019-09-02 | 2019-11-29 | 哈尔滨工业大学 | Small and micro-satellite navigation attitude measuring system dynamic comprehensive performance testing device and method |
| WO2020019260A1 (en) * | 2018-07-26 | 2020-01-30 | 深圳市大疆创新科技有限公司 | Calibration method for magnetic sensor, control terminal and movable platform |
| CN112964278A (en) * | 2021-03-25 | 2021-06-15 | 北京三快在线科技有限公司 | Method, device, electronic equipment and storage medium for determining calibration parameters of magnetometer |
| CN113514789A (en) * | 2021-04-23 | 2021-10-19 | 北京大学 | Magnetic sensor array calibration method |
| CN114325536A (en) * | 2021-12-22 | 2022-04-12 | 重庆金山医疗技术研究院有限公司 | Magnetic field calibration method and related assembly |
| CN114415261A (en) * | 2021-12-10 | 2022-04-29 | 华中光电技术研究所（中国船舶重工集团公司第七一七研究所） | Rapid calibration method for portable relative gravimeter |
| CN115507849A (en) * | 2022-11-22 | 2022-12-23 | 北京理工大学前沿技术研究院 | Magnetic sensor correction method and system based on INS/GNSS combined navigation assistance |
| CN117933097A (en) * | 2024-03-21 | 2024-04-26 | 国网江西省电力有限公司电力科学研究院 | Intelligent measuring method for magnetic field strength of overhead transmission line |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104613983A (en) * | 2015-02-03 | 2015-05-13 | 中国航天时代电子公司 | Whole machine magnetometer calibration method applied to micro unmanned plane |
-
2017
- 2017-12-07 CN CN201711289238.0A patent/CN107894241A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104613983A (en) * | 2015-02-03 | 2015-05-13 | 中国航天时代电子公司 | Whole machine magnetometer calibration method applied to micro unmanned plane |
Non-Patent Citations (2)
| Title |
|---|
| 张海鹰 等: "基于椭球拟合三轴加速度计误差补偿方法", 《传感器世界》 * |
| 王庆宾 等: "三轴磁传感器快速标定方法研究", 《中国测试》 * |
Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108761548A (en) * | 2018-05-25 | 2018-11-06 | 哈尔滨工程大学 | The miniature magnetometers magnetic disturbance backoff algorithm of constraint least square ellipsoid fitting |
| CN109059960A (en) * | 2018-07-18 | 2018-12-21 | 福州大学 | A kind of calibration method of three-dimensional electronic compass |
| CN109059960B (en) * | 2018-07-18 | 2021-08-31 | 福州大学 | Calibration method of three-dimensional electronic compass |
| WO2020019260A1 (en) * | 2018-07-26 | 2020-01-30 | 深圳市大疆创新科技有限公司 | Calibration method for magnetic sensor, control terminal and movable platform |
| CN110770539A (en) * | 2018-07-26 | 2020-02-07 | 深圳市大疆创新科技有限公司 | Magnetic sensor calibration method, control terminal and movable platform |
| CN109238262B (en) * | 2018-11-05 | 2020-10-30 | 珠海全志科技股份有限公司 | Anti-interference method for course attitude calculation and compass calibration |
| CN109238262A (en) * | 2018-11-05 | 2019-01-18 | 珠海全志科技股份有限公司 | A kind of course attitude algorithm and compass calibrate anti-interference method |
| CN109781144B (en) * | 2019-01-30 | 2021-03-19 | 京东方科技集团股份有限公司 | Data correction method and device, electronic equipment and computer readable storage medium |
| CN109781144A (en) * | 2019-01-30 | 2019-05-21 | 京东方科技集团股份有限公司 | Data correcting method, device, electronic equipment and computer readable storage medium |
| US11526580B2 (en) | 2019-01-30 | 2022-12-13 | Beijing Boe Optoelectronics Technology Co., Ltd. | Data correction method and apparatus, electronic device and computer-readable storage medium |
| CN110398702B (en) * | 2019-06-19 | 2021-07-23 | 北京摩高科技有限公司 | Real-time online magnetic calibration method based on multi-sensor fusion |
| CN110398702A (en) * | 2019-06-19 | 2019-11-01 | 北京摩高科技有限公司 | A kind of real-time online magnetic calibration method based on Multi-sensor Fusion |
| CN110514228A (en) * | 2019-09-02 | 2019-11-29 | 哈尔滨工业大学 | Small and micro-satellite navigation attitude measuring system dynamic comprehensive performance testing device and method |
| CN112964278A (en) * | 2021-03-25 | 2021-06-15 | 北京三快在线科技有限公司 | Method, device, electronic equipment and storage medium for determining calibration parameters of magnetometer |
| CN113514789A (en) * | 2021-04-23 | 2021-10-19 | 北京大学 | Magnetic sensor array calibration method |
| CN114415261A (en) * | 2021-12-10 | 2022-04-29 | 华中光电技术研究所（中国船舶重工集团公司第七一七研究所） | Rapid calibration method for portable relative gravimeter |
| CN114325536A (en) * | 2021-12-22 | 2022-04-12 | 重庆金山医疗技术研究院有限公司 | Magnetic field calibration method and related assembly |
| CN115507849A (en) * | 2022-11-22 | 2022-12-23 | 北京理工大学前沿技术研究院 | Magnetic sensor correction method and system based on INS/GNSS combined navigation assistance |
| CN117933097A (en) * | 2024-03-21 | 2024-04-26 | 国网江西省电力有限公司电力科学研究院 | Intelligent measuring method for magnetic field strength of overhead transmission line |
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