CN111780786A - Online calibration method for three-axis TMR sensor - Google Patents
Online calibration method for three-axis TMR sensor Download PDFInfo
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- CN111780786A CN111780786A CN202010791964.8A CN202010791964A CN111780786A CN 111780786 A CN111780786 A CN 111780786A CN 202010791964 A CN202010791964 A CN 202010791964A CN 111780786 A CN111780786 A CN 111780786A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R35/00—Testing or calibrating of apparatus covered by the other groups of this subclass
- G01R35/005—Calibrating; Standards or reference devices, e.g. voltage or resistance standards, "golden" references
- G01R35/007—Standards or reference devices, e.g. voltage or resistance standards, "golden references"
Abstract
The invention relates to an on-line calibration method of a three-axis TMR sensor, which comprises a TMR sensor, an X axis, a Y axis and a Z axis, and comprises the following operation steps: initializing parameters, rotating the horizontal rotating body, repeatedly acquiring a pitch angle theta and a roll angle gamma detected by an inertial navigation system and three-axis output M of a TMR magnetic sensor in a body coordinate system in the rotating processX,MY,MZ(ii) a Establishing an elliptical orbit model of the original magnetic field intensity vector rotation in a horizontal plane, and fitting based on a least square method to obtain magnetic calibration parameters; c, after the body rotates horizontally for one circle, based on the multiple groups of magnetic field intensity vectors H obtained in the step c1And e, compensating the elliptical track into a circular track based on the magnetic calibration parameters obtained in the step e, and calculating the magnetic field intensity after compensation. In short, the technical scheme of the application utilizes excellent optimization scheme, and solves the problem that the traditional magnetic sensor has calibration errors.
Description
Technical Field
The invention relates to the technical field of magnetic sensor application, in particular to an online calibration method for a three-axis TMR sensor.
Background
The combination of inertia/geomagnetism is widely used as a navigation mode with lower cost in the fields of automatic driving and control of unmanned aerial vehicles, unmanned ships, unmanned vehicles and the like, wherein a magnetic sensor is a core element of geomagnetism navigation, the magnetic heading is calculated by sensing the direction of the geomagnetism vector, and the error accumulation caused by inertial navigation is corrected according to the magnetic heading, and the magnetic field intensity of the earth is very weak and only about 0.5 gauss is provided, so that the interference of an external magnetic field is easily caused, for example, in the inertia/geomagnetism combined navigation of an underwater unmanned underwater vehicle, the precision of the geomagnetism navigation is reduced due to the severe geomagnetic interference due to the complex external magnetic field environment during navigation, and the precision of a combined navigation system is further reduced, so when a magnetic sensitive device is used, the magnetic calibration must be carried out in the using environment, and the influence of various external magnetic interferences is eliminated.
The TMR (tunnel magnetoresistive resistance) element is a novel magnetoresistive effect sensor which is applied to the industry in recent years, the TMR element utilizes the tunnel magnetoresistive effect of a magnetic multilayer film material to sense a magnetic field, and the TMR element has the advantages of high magnetic field sensitivity, large magnetoresistive change rate, good linearity, good temperature stability, stable performance and no interlayer coupling effect, does not need an additional magnetic gathering ring structure and a Set/Reset coil structure, and can be made into various magnetic sensors with high sensitivity, small volume and convenient use, so the TMR sensor is gradually applied to an inertia/geomagnetic combined navigation system of an underwater unmanned underwater vehicle, therefore, the on-line calibration method of the triaxial TMR sensor is designed, and the on-line calibration method is urgently needed for the technical field of application of the current magnetic sensors.
Disclosure of Invention
In view of this, the present invention provides a combined calibration scheme based on two least square fits and using a calibrated accelerometer to calibrate a TMR sensor, so as to solve the problem of the deviation of the sensitive axis of a three-axis TMR sensor under the interference of a complex external magnetic field, which can improve the measurement accuracy of the TMR sensor in the complex magnetic field environment, and solve the problem of the misalignment of the sensitive axis of a acceleration sensor and a magnetic sensor in the system.
The invention is realized by the following technical scheme:
a three-axis TMR sensor online calibration method comprises a TMR sensor, an X axis, a Y axis and a Z axis, and comprises the following operation steps:
a. initializing parameters, rotating the horizontal rotating body, repeatedly acquiring a pitch angle theta and a roll angle gamma detected by an inertial navigation system and three-axis output M of a TMR magnetic sensor in a body coordinate system in the rotating processX,MY,MZ；
b. Calculating original magnetic field intensity vectors in a plurality of groups of horizontal planes according to the parameters acquired in the step a
c. Establishing an elliptical orbit model of the original magnetic field intensity vector rotation in a horizontal plane, and fitting based on a least square method to obtain magnetic calibration parameters;
d. c, after the body rotates horizontally for one circle, based on the multiple groups of magnetic field intensity vectors H obtained in the step c1The formed elliptic track is compensated into a circular track to obtain a magnetic field intensity vector H2；
e. D, vector H in step d is subjected to least square method2Fitting is carried out, and magnetic calibration parameters are obtained again;
f. e, compensating the elliptical track into a circular track based on the magnetic calibration parameters obtained in the step e, and calculating the magnetic field intensity after compensation;
g. the calibrated acceleration sensor and the TMR magnetic sensor to be detected are placed in the same detection environment, detection data of the acceleration sensor and the TMR magnetic sensor to be detected are obtained, and an identity equation of the detection system is obtained according to the theory that points of detected acceleration information and magnetic field information are multiplied by constants.
Further, in the step b, magnetic field vectors in a plurality of groups of horizontal planes are calculated
The method specifically comprises the following steps:
further, the step c specifically includes setting any ellipse equation in the plane as:
x2+Axy+By2+Cx+Dy+E＝0
wherein A, B, C, D, E is the equation coefficient, and the objective function is established as:
wherein n is the number of ellipses, order
The parameters of the magnetic calibration are calculated based on the values of the least squares solution A, B, C, D, E,
wherein the content of the first and second substances,
A. b, C, D, E are respectively quadratic term coefficient, first order term coefficient and constant term coefficient of plane arbitrary ellipse equation;
Bx,Bythe magnetic offsets at the X, Y axis due to hard magnetic interference, respectively;
φSis the rotation angle caused by soft magnetic interference;
Kx,Kyare respectively the scale coefficients on the x and y axes, so that the calibrated magnetic field intensity vector rotation track is
A standard circle;
thus obtaining H1Corresponding parameter A1,B1,C1,D1,E1The value of (b), i.e. the coefficient of the elliptical orbit model of the original magnetic field strength vector rotation, is also based on the obtained A1,B1,C1,D1,E1Value of (d) to obtain a magnetic calibration parameter (B)x1,By1，Kx1,Ky1,φS1。
Further, the step d specifically includes calculating the magnetic field strength vector when the body rotates horizontally for one circle
Comprises the following steps:
further, the step e specifically includes: for the obtained multiple groups Hx2,Hy2Data, calculating again by least square method to obtain parameter A1,B1,C1,D1,E1Fitting the coefficients of the obtained elliptical trajectory model of the vector rotation of the magnetic field strength again, and obtaining A1,B1,C1,D1,E1Magnetic calibration parameter B obtained by calculating the value ofx2,By2，Kx2,Ky2,φS2。
Further, the magnetic field intensity compensated in the step f is as follows:
further, the identity and the function in step g are respectively:
wherein u isiThe input of the magnetic sensor is the output value of the magnetic sensor after the calibration is finished theoretically;
a is a gravity value measured after the acceleration sensor is calibrated;
y represents a sensor output vector;
h represents a composite error matrix of the magnetic sensor;
biasis a bias of the magnetic sensor;
solving to obtain the detection result of the magnetic sensor by a least square method; wherein L is H-1,d＝H-1·bias(ii) a Calculating to obtain a magnetic heading angle according to the compensated magnetic field intensity
The invention has the beneficial effects that:
according to the online calibration method for the three-axis TMR sensor, the problem of complex magnetic field calibration is solved by performing fitting twice, then gravity field information is fully utilized, the effect that the sensitive axis of the magnetic sensor and the sensitive axis of the accelerometer are kept consistent is achieved, accurate calibration of a magnetic field in the true sense is achieved, and the maintenance cost of operation can be reduced.
In short, the technical scheme of the application utilizes the optimized algorithm, and solves the problem that the traditional magnetic sensor has calibration errors.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objectives and other advantages of the invention may be realized and attained by the means of the instrumentalities and combinations particularly pointed out hereinafter.
Drawings
FIG. 1 is a flow chart of an on-line calibration implementation of the present invention;
FIG. 2 is a calibration implementation layout of the present invention;
FIG. 3 is a schematic view of three-axis attitude corner coordinates of the present invention;
fig. 4 is a schematic output diagram of the tri-axial TMR sensor of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below, and it is obvious that the described embodiments are a part of the embodiments of the present invention, but not all of the embodiments.
Thus, the following detailed description of the embodiments of the present invention is not intended to limit the scope of the invention as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the above description of the present invention, it should be noted that the terms "one side", "the other side" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings or orientations or positional relationships that the products of the present invention are conventionally placed in use, and are only used for convenience in describing the present invention and simplifying the description, but do not indicate or imply that the device or the element to which the present invention is directed must have a specific orientation, be constructed in a specific orientation, and be operated, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and the like are used merely to distinguish one description from another, and are not to be construed as indicating or implying relative importance.
Further, the term "identical" and the like do not mean that the components are absolutely required to be identical, but may have slight differences. The term "perpendicular" merely means that the positional relationship between the components is more perpendicular than "parallel", and does not mean that the structure must be perfectly perpendicular, but may be slightly inclined.
The invention provides a technical scheme that: a three-axis TMR sensor online calibration method comprises a TMR sensor, an X axis, a Y axis and a Z axis, and comprises the following operation steps:
a. initializing parameters, rotating the horizontal rotating body, repeatedly acquiring a pitch angle theta and a roll angle gamma detected by an inertial navigation system and three-axis output M of a TMR magnetic sensor in a body coordinate system in the rotating processX,MY,MZ；
b. Calculating original magnetic field intensity vectors in a plurality of groups of horizontal planes according to the parameters acquired in the step a
c. Establishing an elliptical orbit model of the original magnetic field intensity vector rotation in a horizontal plane, and fitting based on a least square method to obtain magnetic calibration parameters;
d. c, after the body rotates horizontally for one circle, based on the multiple groups of magnetic field intensity vectors H obtained in the step c1The formed elliptic track is compensated into a circular track to obtain a magnetic field intensity vector H2；
e. D, vector H in step d is subjected to least square method2Fitting is carried out, and magnetic calibration parameters are obtained again;
f. e, compensating the elliptical track into a circular track based on the magnetic calibration parameters obtained in the step e, and calculating the magnetic field intensity after compensation;
g. the calibrated acceleration sensor and the TMR magnetic sensor to be detected are placed in the same detection environment, detection data of the acceleration sensor and the TMR magnetic sensor to be detected are obtained, and an identity equation of the detection system is obtained according to the theory that points of detected acceleration information and magnetic field information are multiplied by constants.
In the invention: in the step b, magnetic field vectors in a plurality of groups of horizontal planes are calculated
The method specifically comprises the following steps:
in the invention: the step c specifically includes setting any ellipse equation in the plane as:
x2+Axy+By2+Cx+Dy+E＝0
wherein A, B, C, D, E is the equation coefficient, and the objective function is established as:
wherein n is the number of ellipses, order
The parameters of the magnetic calibration are calculated based on the values of the least squares solution A, B, C, D, E,
wherein the content of the first and second substances,
A. b, C, D, E are respectively quadratic term coefficient, first order term coefficient and constant term coefficient of plane arbitrary ellipse equation;
Bx,Bythe magnetic offsets at the X, Y axis due to hard magnetic interference, respectively;
φSis the rotation angle caused by soft magnetic interference;
Kx,Kyare respectively the scale coefficients on the x and y axes, so that the calibrated magnetic field intensity vector rotation track is
A standard circle;
thus obtaining H1Corresponding parameter A1,B1,C1,D1,E1The value of (b), i.e. the coefficient of the elliptical orbit model of the original magnetic field strength vector rotation, is also based on the obtained A1,B1,C1,D1,E1Value of (d) to obtain a magnetic calibration parameter (B)x1,By1，Kx1,Ky1,φS1。
In the invention: step d specifically comprises the step of calculating to obtain a magnetic field intensity vector when the body rotates horizontally for one circle
Comprises the following steps:
in the invention: the step e specifically comprises the following steps: for the obtained multiple groups Hx2,Hy2Data, calculating again by least square method to obtain parameter A1,B1,C1,D1,E1Fitting the coefficients of the obtained elliptical trajectory model of the vector rotation of the magnetic field strength again, and obtaining A1,B1,C1,D1,E1Calculating the value ofMagnetic calibration parameter Bx2,By2，Kx2,Ky2,φS2。
In the invention: the magnetic field intensity compensated in the step f is as follows:
in the present invention, the identity and the function in step g are respectively:
wherein u isiThe input of the magnetic sensor is the output value of the magnetic sensor after the calibration is finished theoretically;
a is a gravity value measured after the acceleration sensor is calibrated;
y represents a sensor output vector;
h represents a composite error matrix of the magnetic sensor;
biasis a bias of the magnetic sensor;
solving to obtain the detection result of the magnetic sensor by a least square method; wherein L is H-1,d＝H-1·bias(ii) a Calculating to obtain a magnetic heading angle according to the compensated magnetic field intensity
Finally, the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all of them should be covered in the claims of the present invention.
Claims (7)
1. A three-axis TMR sensor online calibration method comprises a TMR sensor, an X axis, a Y axis and a Z axis, and is characterized in that: the TMR sensor calibration method comprises the following operation steps:
a. initializing parameters, rotating the horizontal rotating body, repeatedly acquiring a pitch angle theta and a roll angle gamma detected by an inertial navigation system and three-axis output M of a TMR magnetic sensor in a body coordinate system in the rotating processX,MY,MZ；
b. Calculating original magnetic field intensity vectors in a plurality of groups of horizontal planes according to the parameters acquired in the step a
c. Establishing an elliptical orbit model of the original magnetic field intensity vector rotation in a horizontal plane, and fitting based on a least square method to obtain magnetic calibration parameters;
d. c, after the body rotates horizontally for one circle, based on the multiple groups of magnetic field intensity vectors H obtained in the step c1The formed elliptic track is compensated into a circular track to obtain a magnetic field intensity vector H2；
e. D, vector H in step d is subjected to least square method2Fitting is carried out, and magnetic calibration parameters are obtained again;
f. e, compensating the elliptical track into a circular track based on the magnetic calibration parameters obtained in the step e, and calculating the magnetic field intensity after compensation;
g. the calibrated acceleration sensor and the TMR magnetic sensor to be detected are placed in the same detection environment, detection data of the acceleration sensor and the TMR magnetic sensor to be detected are obtained, and an identity equation of the detection system is obtained according to the theory that points of detected acceleration information and magnetic field information are multiplied by constants.
2. The on-line calibration method for the three-axis TMR sensor according to claim 1, wherein: in the step b, magnetic field vectors in a plurality of groups of horizontal planes are calculated
The method specifically comprises the following steps:
3. the on-line calibration method for the three-axis TMR sensor according to claim 1, wherein: the step c specifically includes setting any ellipse equation in the plane as:
x2+Axy+By2+Cx+Dy+E＝0
wherein A, B, C, D, E is the equation coefficient, and the objective function is established as:
wherein n is the number of ellipses, order
The parameters of the magnetic calibration are calculated based on the values of the least squares solution A, B, C, D, E,
wherein the content of the first and second substances,
A. b, C, D, E are respectively quadratic term coefficient, first order term coefficient and constant term coefficient of plane arbitrary ellipse equation;
Bx,Bythe magnetic offsets at the X, Y axis due to hard magnetic interference, respectively;
φSis the rotation angle caused by soft magnetic interference;
Kx,Kythe calibration coefficients are respectively on the x axis and the y axis, so that the rotation track of the magnetic field intensity vector after calibration is a standard circle;
thus obtaining H1Corresponding parameter A1,B1,C1,D1,E1The value of (b), i.e. the coefficient of the elliptical orbit model of the original magnetic field strength vector rotation, is also based on the obtained A1,B1,C1,D1,E1Value of (d) to obtain a magnetic calibration parameter (B)x1,By1，Kx1,Ky1,φS1。
4. The on-line calibration method for the three-axis TMR sensor according to claim 1, wherein: step d specifically comprises the step of calculating to obtain a magnetic field intensity vector when the body rotates horizontally for one circle
Comprises the following steps:
5. the on-line calibration method for the three-axis TMR sensor according to claim 1, wherein: the step e specifically comprises the following steps: for the obtained multiple groups Hx2,Hy2Data, calculating again by least square method to obtain parameter A1,B1,C1,D1,E1Fitting the coefficients of the obtained elliptical trajectory model of the vector rotation of the magnetic field strength again, and obtaining A1,B1,C1,D1,E1Magnetic calibration parameter B obtained by calculating the value ofx2,By2，Kx2,Ky2,φS2。
6. The on-line calibration method for the three-axis TMR sensor according to claim 1, wherein: the magnetic field intensity compensated in the step f is as follows:
7. the on-line calibration method for the three-axis TMR sensor according to claim 1, wherein: the identity equation and the function formula in the step g are respectively as follows:
wherein u isiThe input of the magnetic sensor is the output value of the magnetic sensor after the calibration is finished theoretically;
a is a gravity value measured after the acceleration sensor is calibrated;
y represents a sensor output vector;
h represents a composite error matrix of the magnetic sensor;
biasis a bias of the magnetic sensor;
solving to obtain the detection result of the magnetic sensor by a least square method; wherein the content of the first and second substances,
L＝H-1,d＝H-1·bias(ii) a Calculating to obtain a magnetic heading angle according to the compensated magnetic field intensity
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112284382A (en) * | 2020-10-23 | 2021-01-29 | 哈尔滨工程大学 | Combined navigation information processing device and underwater navigation system |
| CN112305473A (en) * | 2020-10-23 | 2021-02-02 | 哈尔滨工程大学 | Calibration method of three-axis TMR sensor |
| CN112985461A (en) * | 2021-03-25 | 2021-06-18 | 成都纵横自动化技术股份有限公司 | Magnetic sensor calibration method based on GNSS direction finding |
| CN113189527A (en) * | 2021-03-20 | 2021-07-30 | 哈尔滨工业大学 | Method for calibrating uniform magnetic source |
| CN113624253A (en) * | 2021-07-24 | 2021-11-09 | 南京理工大学 | Rotator error compensation and experiment method for three-axis magnetic sensor |
| CN113640726A (en) * | 2021-10-19 | 2021-11-12 | 青岛杰瑞自动化有限公司 | Multi-azimuth ellipse fitting calibration method and system for double-shaft magnetometer |
| 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 |
| CN114812532A (en) * | 2022-05-30 | 2022-07-29 | 天津云圣智能科技有限责任公司 | Magnetic compass parameter calibration method, unmanned aerial vehicle course angle determination method and device |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112284382A (en) * | 2020-10-23 | 2021-01-29 | 哈尔滨工程大学 | Combined navigation information processing device and underwater navigation system |
| CN112305473A (en) * | 2020-10-23 | 2021-02-02 | 哈尔滨工程大学 | Calibration method of three-axis TMR sensor |
| CN112305473B (en) * | 2020-10-23 | 2023-08-11 | 哈尔滨工程大学 | Calibration method of triaxial TMR sensor |
| CN113189527A (en) * | 2021-03-20 | 2021-07-30 | 哈尔滨工业大学 | Method for calibrating uniform magnetic source |
| CN112985461A (en) * | 2021-03-25 | 2021-06-18 | 成都纵横自动化技术股份有限公司 | Magnetic sensor calibration method based on GNSS direction finding |
| CN112985461B (en) * | 2021-03-25 | 2023-11-03 | 成都纵横自动化技术股份有限公司 | GNSS direction finding based magnetic sensor calibration method |
| CN113624253A (en) * | 2021-07-24 | 2021-11-09 | 南京理工大学 | Rotator error compensation and experiment method for three-axis magnetic sensor |
| CN113640726A (en) * | 2021-10-19 | 2021-11-12 | 青岛杰瑞自动化有限公司 | Multi-azimuth ellipse fitting calibration method and system for double-shaft magnetometer |
| CN113640726B (en) * | 2021-10-19 | 2021-12-21 | 青岛杰瑞自动化有限公司 | Multi-azimuth ellipse fitting calibration method and system for double-shaft magnetometer |
| 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 |
| CN114812532A (en) * | 2022-05-30 | 2022-07-29 | 天津云圣智能科技有限责任公司 | Magnetic compass parameter calibration method, unmanned aerial vehicle course angle determination method and device |
| CN114812532B (en) * | 2022-05-30 | 2022-10-11 | 天津云圣智能科技有限责任公司 | Magnetic compass parameter calibration method and unmanned aerial vehicle course angle determination method and device |
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