CN105928544A - Rapid self-calibration method of micro-inertia measurement combination unit, and apparatus thereof - Google Patents
Rapid self-calibration method of micro-inertia measurement combination unit, and apparatus thereof Download PDFInfo
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Abstract
The invention discloses a rapid self-calibration method of a micro-inertia measurement combination unit, and an apparatus thereof. The method comprises the following steps: acquiring the real-time data information of the micro-inertia measurement combination unit rotating to different positions; processing the real-time data information by using a 3sigma technology to obtain new data information; establishing a micro-inertia measurement combination unit error model; and resolving the new data information through a Levenberg-Marquard algorithm and the micro-inertia measurement combination unit error model to obtain the every error term of the micro-inertia measurement combination unit. The method meets onsite calibration demands, reduces the calibration cost of the micro-inertia measurement combination unit and further improves the calibration precision.
Description
Technical Field
The invention relates to the technical field of inertial measurement, in particular to a quick self-calibration method and device of a micro-inertial measurement combination unit.
Background
The micro-inertia measurement unit comprises a three-axis micro-mechanical gyroscope and a three-axis micro-mechanical accelerometer, the three-axis micro-mechanical gyroscope and the three-axis micro-mechanical acceleration are respectively and orthogonally installed on the fixed base, and the three-axis angular velocity and the acceleration are output through the signal processing and compensation unit and the interface circuit to form the micro-inertia measurement unit which can output the three-axis angular velocity and the three-axis acceleration.
The miniature inertial measurement unit has the advantages of small volume, light weight, long service life, high reliability, low cost, strong environment adaptability and the like, can provide position, speed and attitude information of a motion carrier, and has wide application prospect in the technical field of attitude measurement and control. The development of research work based on workers is of great significance, but some problems still exist and need to be further solved. The precision of the micro-inertia measurement elements, namely the micro-accelerometer and the micro-gyroscope determines the measurement precision of the micro-inertia measurement combination unit, so that the calibration of the micro-inertia measurement combination unit before use has important significance, and parameters such as zero offset error, scale coefficient and the like of each inertia sensor can be determined.
The traditional method for calibrating the micro-inertia measurement combination unit needs to provide a reference by means of a high-precision three-axis turntable, has high requirement on the precision of the turntable, needs long calibration time and high cost, cannot calibrate the micro-inertia measurement combination outside a laboratory, and cannot meet the requirement of on-site calibration.
Disclosure of Invention
The object of the present invention is to solve at least to some extent one of the above mentioned technical problems.
Therefore, the first purpose of the present invention is to provide a method for fast self-calibration of a micro-inertial measurement unit. The method can meet the field calibration requirement, reduce the calibration cost of the micro-inertia measurement combination unit and further improve the calibration precision.
The second purpose of the invention is to provide a quick self-calibration device of the micro-inertia measurement combination unit.
To achieve the above object, a method for fast self-calibration of a micro inertial measurement unit according to an embodiment of the first aspect of the present invention includes the following steps: acquiring real-time data information of the micro-inertia measurement combination unit rotating to different positions; processing the real-time data information by using a 3 sigma method to obtain new data information; establishing an error model of a micro inertial measurement combination unit; and resolving new data information through a Levenberg-Marquard algorithm and a micro-inertia measurement combination unit error model to obtain each error term of the micro-inertia measurement combination unit.
The method for rapidly self-calibrating the micro-inertia measurement combination unit comprises the steps of firstly obtaining real-time data information of the micro-inertia measurement combination unit rotating to different positions, then processing the real-time data information to obtain new data information, establishing an error model of the micro-inertia measurement combination unit, and finally resolving the new data information through a Levenberg-Marquard algorithm and an error model of the micro-inertia measurement combination unit to obtain each error item of the micro-inertia measurement combination unit. The method can meet the field calibration requirement, reduce the calibration cost of the micro-inertia measurement combination unit and further improve the calibration precision.
In some examples, the processing of the real-time data information using the 3 σ method results in a newThe data information specifically includes: calculating the mean value of the real-time data information asAndcalculating the residual error of the real-time data information as Andcalculating the standard deviation of the real-time data information as Andif the measured value x in the real-time data informationd(1≤d≤n)、yd(1. ltoreq. d. ltoreq. n) and zdThe residual errors (d is more than or equal to 1 and less than or equal to n) respectively satisfy the following conditions:andthe outlier is removed.
In some examples, the establishing a micro inertial measurement unit error model includes establishing an error model of a micro-mechanical accelerometer and a micro-mechanical gyroscope of the micro inertial measurement unit; wherein, the measurement model of the micro-mechanical accelerometer is as follows: f is SaNaa+ba+aWherein f is the accelerometer measurementA is the acceleration input, baIs the zero offset, S, of the accelerometeraIs the scale factor of the accelerometer, NaFor the mounting alignment factor of the accelerometer,ameasurement noise for the accelerometer; the measurement model of the micromechanical gyroscope is as follows: omegag＝SgNgω+bg+gWherein ω isgIs the measured value of the gyroscope, omega is the angular velocity input, bgIs zero offset, S, of the gyroscopegIs the scale factor of the gyroscope, NgFor the mounting alignment factor of the gyroscope,gis the measurement noise of the gyroscope.
In some examples, the Levenberg-Marquard algorithm is mathematically modeled asWherein S is an independent variable, gkIs a gradient, GkIs a Hesse matrix and hkIs the confidence domain radius of the kth iteration.
In some examples, the fast self-calibration method further includes: and analyzing and compensating each error term.
To achieve the above object, the present invention provides a fast self-calibration apparatus for micro inertial measurement unit according to a second aspect, comprising: the acquisition module is used for acquiring real-time data information of the micro-inertia measurement combination unit rotating to different positions; the processing module is used for processing the real-time data information by using a 3 sigma method to obtain new data information; the establishing module is used for establishing an error model of the micro inertial measurement combination unit; and the resolving module is used for resolving the new data information through a Levenberg-Marquard algorithm and the micro-inertia measurement combination unit error model to obtain each error item of the micro-inertia measurement combination unit.
The quick self-calibration device of the micro-inertia measurement combination unit comprises an acquisition module, a processing module, a building module, a resolving module and a calibration module, wherein the acquisition module acquires real-time data information of the micro-inertia measurement combination unit rotating to different positions, the processing module processes the real-time data information to acquire new data information, the building module builds an error model of the micro-inertia measurement combination unit, and the resolving module resolves the new data information through a Levenberg-Marquard algorithm and the error model of the micro-inertia measurement combination unit to acquire each error item of the micro-inertia measurement combination unit. The device can meet the field calibration requirement, reduce the calibration cost of the micro-inertia measurement combination unit, and further improve the calibration precision.
In some examples, the processing module is specifically configured to: calculating the mean value of the real-time data information asAndcalculating the residual error of the real-time data information asAndcalculating the standard deviation of the real-time data information asAndif the measured value x in the real-time data informationd(1≤d≤n)、yd(1. ltoreq. d. ltoreq. n) and zdThe residual errors (d is more than or equal to 1 and less than or equal to n) respectively satisfy the following conditions:andthe outlier is removed.
In some examples, the establishing module further comprises a micro-mechanical accelerometer and a micro-inertial measurement unit of the micro-inertial measurement unitEstablishing an error model by a mechanical gyroscope; wherein, the measurement model of the micro-mechanical accelerometer is as follows: f is SaNaa+ba+aWhere f is the accelerometer measurement, a is the acceleration input, baIs the zero offset, S, of the accelerometeraIs the scale factor of the accelerometer, NaFor the mounting alignment factor of the accelerometer,ameasurement noise for the accelerometer; the measurement model of the micromechanical gyroscope is as follows: omegag＝SgNgω+bg+gWherein ω isgIs the measured value of the gyroscope, omega is the angular velocity input, bgIs zero offset, S, of the gyroscopegIs the scale factor of the gyroscope, NgFor the mounting alignment factor of the gyroscope,gis the measurement noise of the gyroscope.
In some examples, the Levenberg-Marquard algorithm is mathematically modeled asWherein S is an independent variable, gkIs a gradient, GkIs a Hesse matrix and hkIs the confidence domain radius of the kth iteration.
In some examples, the fast self-calibration apparatus further includes: and the analysis compensation module is used for analyzing and compensating each error item.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
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The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a flow chart of a method for fast self-calibration of a micro-inertial measurement unit assembly according to one embodiment of the present invention;
FIG. 2 is a schematic structural diagram of a micro inertial measurement unit according to one embodiment of the present invention;
FIG. 3 is a comparison graph of the fast self-calibration method of the micro inertial measurement unit and the conventional calibration method after position compensation according to an embodiment of the present invention;
FIG. 4 is a comparison graph of the micro inertial measurement unit after angle compensation for the fast self-calibration method and the conventional calibration method according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a fast self-calibration arrangement of a micro-inertial measurement unit according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
By designing different overturning positions, overturning angles and overturning sequences and combining the static or constant angular speed input of the micro-inertia measurement unit, the output vector sum of the triaxial micro-inertia accelerometer and the triaxial micro-inertia gyroscope has an identity relation. And (3) solving an equation by using a numerical value solving method through overturning a plurality of positions to obtain each error parameter of the micro-inertia measurement combination.
FIG. 1 is a flow chart of a method for fast self-calibration of a micro-inertial measurement unit according to one embodiment of the present invention.
As shown in fig. 1, the method for fast self-calibration of the micro inertial measurement unit may include:
in step 101, real-time data information of the micro inertial measurement unit rotating to different positions is obtained.
Specifically, the micro-inertia measurement combination unit is fixed on a special tool hexahedral clamp, relative movement is guaranteed not to occur, and real-time data information of the micro-inertia measurement combination unit, which is turned to different positions, is collected through a data collection system.
It should be noted that, the connection of the data acquisition unit, the upper computer, the connector, etc. is determined, whether the line is correct is checked, and the system is powered on after no error is checked. And turning the micro-inertia measurement combination unit for multiple times according to the preset turning position, the turning angle and the turning sequence. Meanwhile, in order to ensure the data output quantity and the data output accuracy, the data acquisition is ensured to be more than 3 minutes at each position, and the micro-inertia combination unit stored at each position outputs data.
The following specifically describes the fast calibration turning path of the micro inertial measurement unit with reference to table 1. As shown in table 1:
TABLE 1 quick calibration and turnover path of micro-inertia measurement combination unit
More specifically, the output of real-time data information of the micro-inertia measurement combination unit at different positions can be acquired at high speed.
In order to make the micro inertial measurement unit more understandable to those skilled in the art, the following description is provided in conjunction with fig. 2. As shown in fig. 2, the micro-mechanical gyroscope and the micro-mechanical accelerometer are comprised, the micro-mechanical gyroscope and the micro-mechanical accelerometer are respectively orthogonally installed on a fixed base, and output three-axis angular velocity and acceleration through a signal processing and compensating unit and an interface circuit to form a micro-inertial measurement unit capable of outputting three-axis angular velocity and three-axis acceleration.
In step 102, the real-time data information is processed by the 3 σ method to obtain new data information.
Specifically, the average value of the real-time data information is calculated asAndcalculating the residual error of the real-time data information as Andcalculating the standard deviation of the real-time data information as Andif measured value x in real-time data informationd(1≤d≤n)、yd(1. ltoreq. d. ltoreq. n) and zdThe residual errors (d is more than or equal to 1 and less than or equal to n) respectively satisfy the following conditions:andthe outlier is removed.
In step 103, a micro inertial measurement unit error model is built.
Specifically, error models are respectively established for the micro-accelerometer and the micro-gyroscope of the micro-inertial measurement combination unit, as follows:
the measurement model of the micro-mechanical accelerometer is as follows: f is SaNaa+ba+a。
Where f is the accelerometer measurement, a is the acceleration input, baIs the zero offset, S, of the accelerometeraIs the scale factor of the accelerometer, NaFor the mounting alignment factor of the accelerometer,ais the measurement noise of the accelerometer.
The measurement model of the micromechanical gyroscope is: omegag＝SgNgω+bg+g。
Wherein, ω isgIs the measured value of the gyroscope, omega is the angular velocity input, bgIs zero offset, S, of the gyroscopegIs the scale factor of the gyroscope, NgFor the mounting alignment factor of the gyroscope,gis the measurement noise of the gyroscope. And (3) obtaining the angular speed and the acceleration of the body through coordinate conversion and output of the micro inertial measurement unit, wherein the angular speed and the acceleration are shown in the formulas (1) and (2):
Kaand KgRespectively expressing the scale factors and the installation alignment relation of the accelerometer combination and the gyroscope combination, and if the angles between the sensitive axes of the gyroscope and the accelerometer and the axis of the body coordinate system are small angles, then
WhereinThe alignment error angle of the ith axis and the jth axis of the accelerometer combination of the body coordinate system is shown,and (4) an alignment error angle of the ith axis of the body coordinate system and the jth axis of the gyroscope combination. f. of0And ω0The zero bias effect of the accelerometer combination and the gyroscope combination is expressed respectively:ξaand ξgThe noise effect of the accelerometer combination and the gyroscope combination is expressed respectively.
In step 104, new data information is resolved through a Levenberg-Marquard algorithm and a micro-inertia measurement combination unit error model to obtain each error item of the micro-inertia measurement combination unit.
Specifically, when the micro inertial measurement unit is stationary or a constant angular velocity is input, there is an identity relationship, as shown in equations (3) and (4):
wherein g is the gravity acceleration value gx、gyAnd gzAcceleration input, theta, respectively, of a three-axis accelerometera、γaAndrespectively the included angles between the ideal sensitive axis of the triaxial accelerometer and the gravity vector. OmegarAs input value of angular velocity, omegarx、ωryAnd ωrzRespectively, the angular velocity input, theta, of a three-axis gyroscopeg、γgAndare respectively three axesAnd the included angle between the ideal sensitive axis of the gyroscope and the input vector of the angular velocity.
According to the micro-inertia measurement combination error model and the micro-inertia measurement combination unit identity equation, solving an error term for multiple times of overturning, namely solving:andand (5) optimal solution.
And solving the optimal value of the nonlinear equation set by adopting a Levenberg-Marquard algorithm. The mathematical model of the LM algorithm isCombining the mathematical model of LM, and solving the nonlinear optimal problem according to the following steps: from an initial point x0，μ0>0 starts iteration, and when the K step is reached, x is calculatedkAnd muk(ii) a Decomposition matrix Gk+μkI, if it is incorrect, let μk＝4μkAnd repeating until the positive definite; solving a system of linear equations (G)k+μkI)sk＝-gkGo out of skAnd calculate rk(ii) a If rk<0.25, let muk+1＝4μk(ii) a If rk>0.75, let muk+1＝μk2; if rk is more than or equal to 0.25 and less than or equal to 0.75, let muk+1＝μkIf r isk≦ 0, indicating that the function value has changed (contrary to the optimization goal) towards an increasing rather than decreasing trend, then another xk+1＝xkAnd is combined with rk<The same applies to μ in the case of 0.25kAnd (6) processing. Otherwise, at rk>In the case of 0, xk+1＝xk+sk. When g | | |k||<Where is a specified positive decimal, the gradient at the iteration point tends to 0 as the minimum point is approached.
It should be noted that the Levenberg-Marquard algorithm is a numerical solution method used for obtaining an optimal solution, wherein the algorithm implementation process is relatively complex. It can be understood that the first expression is a quadratic model (optimal solution) for modeling the objective function, and its arguments are s, Gk gradient, Gk is Hesse matrix, hk in the second expression is the upper bound of the confidence domain (or called confidence domain radius) of the kth iteration, so that the second expression indicates that the displacement is within the upper bound of the confidence domain. Further, the norm in the second equation is what norm is not specified.
In order to ensure that the solution of the optimal problem is unique, the number of the overturning positions is not less than the number of undetermined coefficients, the accuracy of the solution can be improved by increasing the number of the overturning positions, and the positions do not need to be strictly aligned unlike the traditional calibration method.
In order to make the skilled person more aware of the results of the method for fast self-calibration of the micro inertial measurement unit according to the embodiment of the present invention, the following description is made with reference to fig. 3 and 4.
As shown in fig. 3, which is a comparison graph of the fast self-calibration method of the micro inertial measurement unit according to an embodiment of the present invention and the traditional calibration method after position compensation, it can be seen that the error between the result of the fast self-calibration method of the micro inertial measurement unit according to the present invention and the result of the traditional calibration method after position compensation is very small.
As shown in fig. 4, a comparison graph of the fast self-calibration method of the micro-inertia measurement combination unit according to an embodiment of the present invention after angle compensation and the traditional calibration method after angle compensation shows that the error between the result of the fast self-calibration method of the micro-inertia measurement combination unit according to the present invention and the result of the traditional calibration method after angle compensation is very small.
In step 105, the individual error terms are analytically compensated.
The method for rapidly self-calibrating the micro-inertia measurement combination unit comprises the steps of firstly obtaining real-time data information of the micro-inertia measurement combination unit rotating to different positions, then processing the real-time data information to obtain new data information, establishing an error model of the micro-inertia measurement combination unit, and finally resolving the new data information through a Levenberg-Marquard algorithm and an error model of the micro-inertia measurement combination unit to obtain each error item of the micro-inertia measurement combination unit. The method can meet the field calibration requirement, reduce the calibration cost of the micro-inertia measurement combination unit and further improve the calibration precision.
Corresponding to the fast self-calibration method for the micro-inertia measurement combination unit provided in the foregoing embodiment, an embodiment of the present invention further provides a fast self-calibration device for controlling the micro-inertia measurement combination unit to suppress sub-synchronous resonance, and since the fast self-calibration device for the micro-inertia measurement combination unit provided in the embodiment of the present invention and the fast self-calibration method for the micro-inertia measurement combination unit provided in the foregoing embodiment have the same or similar technical features, the implementation manner of the fast self-calibration method for the micro-inertia measurement combination unit provided in the foregoing embodiment is also applicable to the fast self-calibration device for the micro-inertia measurement combination unit provided in the present embodiment, and will not be described in detail in the present embodiment. As shown in fig. 5, the fast self-calibration apparatus of the micro inertial measurement unit may include: an acquisition module 10, a processing module 20, a building module 30 and a calculation module 40.
The obtaining module 10 is configured to obtain real-time data information of the micro inertial measurement unit rotating to different positions.
Specifically, the micro-inertia measurement combination unit is fixed on a special tool hexahedral clamp, relative movement is guaranteed not to occur, and real-time data information of the micro-inertia measurement combination unit, which is turned to different positions, is collected through a data collection system.
The processing module 20 is configured to process the real-time data information by using a 3 σ method to obtain new data information.
The building module 30 is used for building an error model of the micro inertial measurement unit.
The resolving module 40 is used for resolving the new data information through a Levenberg-Marquard algorithm and a micro-inertia measurement combination unit error model to obtain each error item of the micro-inertia measurement combination unit.
In some examples, the processing module 20 is specifically configured to: calculating the mean of the real-time data information asAndcalculating the residual error of the real-time data information asAndcalculating the standard deviation of the real-time data information asAndif measured value x in real-time data informationd(1≤d≤n)、yd(1. ltoreq. d. ltoreq. n) and zdThe residual errors (d is more than or equal to 1 and less than or equal to n) respectively satisfy the following conditions: andthe outlier is removed.
In some examples, the establishing module 30 further comprises establishing an error model of the micro-mechanical accelerometer and the micro-mechanical gyroscope of the micro-inertial measurement unit; the measuring model of the micro-mechanical accelerometer is as follows: f is SaNaa+ba+aWhere f is the accelerometer measurement, a is the acceleration input, baIs the zero offset, S, of the accelerometeraIs the scale factor of the accelerometer, NaFor the mounting alignment factor of the accelerometer,ais the measurement noise of the accelerometer. The measurement model of the micromechanical gyroscope is: omegag＝SgNgω+bg+gWherein ω isgIs the measured value of the gyroscope, omega is the angular velocity input, bgIs zero offset, S, of the gyroscopegIs the scale factor of the gyroscope, NgFor the mounting alignment factor of the gyroscope,gis the measurement noise of the gyroscope.
In some examples, the Levenberg-Marquard algorithm is mathematically modeled asWherein S is an independent variable, gkIs a gradient, GkIs a Hesse matrix and hkIs the confidence domain radius of the kth iteration.
In some examples, the fast self-calibration apparatus further includes: the analysis compensation module 50 is used for analyzing and compensating each error term.
The quick self-calibration device of the micro-inertia measurement combination unit comprises an acquisition module, a processing module, a building module, a resolving module and a calibration module, wherein the acquisition module acquires real-time data information of the micro-inertia measurement combination unit rotating to different positions, the processing module processes the real-time data information to acquire new data information, the building module builds an error model of the micro-inertia measurement combination unit, and the resolving module resolves the new data information through a Levenberg-Marquard algorithm and the error model of the micro-inertia measurement combination unit to acquire each error item of the micro-inertia measurement combination unit. The device can meet the field calibration requirement, reduce the calibration cost of the micro-inertia measurement combination unit, and further improve the calibration precision.
In the description of the present invention, it is to be understood that the terms "first", "second" and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (10)
1. A quick self-calibration method of a micro-inertia measurement combination unit is characterized by comprising the following steps:
acquiring real-time data information of the micro-inertia measurement combination unit rotating to different positions;
processing the real-time data information by using a 3 sigma method to obtain new data information;
establishing an error model of a micro inertial measurement combination unit;
and resolving the new data information through a Levenberg-Marquard algorithm and the micro-inertia measurement combination unit error model to obtain each error item of the micro-inertia measurement combination unit.
2. The fast self-calibration method according to claim 1, wherein the processing the real-time data information by using the 3 σ method to obtain new data information specifically comprises:
calculating the mean value of the real-time data information asAnd
calculating the residual error of the real-time data information asAnd
calculating the standard deviation of the real-time data information asAnd
if the measured value x in the real-time data informationd(1≤d≤n)、yd(1. ltoreq. d. ltoreq. n) and zdThe residual errors (d is more than or equal to 1 and less than or equal to n) respectively satisfy the following conditions:andthe outlier is removed.
3. The fast self-calibration method according to claim 1, wherein the establishing of the error model of the micro inertial measurement unit comprises establishing an error model of a micro mechanical accelerometer and a micro mechanical gyroscope of the micro inertial measurement unit; wherein,
the measurement model of the micro-mechanical accelerometer is as follows: f is SaNaa+ba+aWhere f is the accelerometer measurement, a is the acceleration input, baIs the zero offset, S, of the accelerometeraIs the scale factor of the accelerometer, NaFor the mounting alignment factor of the accelerometer,ameasurement noise for the accelerometer;
the measurement model of the micromechanical gyroscope is as follows: omegag＝SgNgω+bg+gWherein ω isgIs the measured value of the gyroscope, omega is the angular velocity input, bgIs zero offset, S, of the gyroscopegIs the scale factor of the gyroscope, NgFor the mounting alignment factor of the gyroscope,gis the measurement noise of the gyroscope.
4. A method for rapid self-calibration according to claim 1, wherein the mathematical model of the Levenberg-Marquard algorithm isWherein S is an independent variable, gkIs a gradient, GkIs a Hesse matrix and hkIs the confidence domain radius of the kth iteration.
5. The method for rapid self-calibration as recited in claim 1, further comprising: and analyzing and compensating each error term.
6. A quick self-calibration device of a micro-inertia measurement combination unit is characterized by comprising:
the acquisition module is used for acquiring real-time data information of the micro-inertia measurement combination unit rotating to different positions;
the processing module is used for processing the real-time data information by using a 3 sigma method to obtain new data information;
the establishing module is used for establishing an error model of the micro inertial measurement combination unit;
and the resolving module is used for resolving the new data information through a Levenberg-Marquard algorithm and the micro-inertia measurement combination unit error model to obtain each error item of the micro-inertia measurement combination unit.
7. The rapid self-calibration apparatus according to claim 6, wherein the processing module is specifically configured to:
calculating the mean value of the real-time data information asAnd
calculating the residual error of the real-time data information asAnd
calculating the standard deviation of the real-time data information asAnd
if the measured value x in the real-time data informationd(1≤d≤n)、yd(1. ltoreq. d. ltoreq. n) and zdThe residual errors (d is more than or equal to 1 and less than or equal to n) respectively satisfy the following conditions:andthe outlier is removed.
8. The rapid self-calibration device according to claim 6, wherein the establishing module further comprises establishing an error model of a micro-mechanical accelerometer and a micro-mechanical gyroscope of the micro-inertial measurement unit; wherein,
the measurement model of the micro-mechanical accelerometer is as follows: f is SaNaa+ba+aWhere f is the accelerometer measurement, a is the acceleration input, baIs the zero offset, S, of the accelerometeraIs the scale factor of the accelerometer, NaFor the mounting alignment factor of the accelerometer,ameasurement noise for the accelerometer;
the measurement model of the micromechanical gyroscope is as follows: omegag＝SgNgω+bg+gWherein ω isgIs the measured value of the gyroscope, omega is the angular velocity input, bgIs zero offset, S, of the gyroscopegIs the scale factor of the gyroscope, NgFor the mounting alignment factor of the gyroscope,gis the measurement noise of the gyroscope.
9. The fast self-calibration apparatus as claimed in claim 6, wherein the mathematical model of the Levenberg-Marquard algorithm isWherein S is an independent variable, gkIs a gradient, GkIs a Hesse matrix and hkIs the confidence domain radius of the kth iteration.
10. The rapid self-calibration apparatus according to claim 6, further comprising: and the analysis compensation module is used for analyzing and compensating each error item.
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