CN116295528A - Nonlinear piecewise temperature compensation method for MEMS gyroscope - Google Patents
Nonlinear piecewise temperature compensation method for MEMS gyroscope Download PDFInfo
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Abstract
The invention provides a nonlinear piecewise temperature compensation method of an MEMS gyroscope, which comprises the following steps: obtaining a plurality of temperature cycle files, determining a data smoothing multiple, performing data smoothing on the temperature cycle data files, identifying a temperature rise and fall process in the temperature cycle data files according to the smoothed plurality of temperature cycle data files, fitting to obtain a corresponding fitting datum line, performing multiple time-relative derivative according to discrete data on the fitting datum line, determining the segmentation point number and segmentation point value of the fitting datum line, obtaining a fitting order, fitting each segment of the fitting datum line to obtain polynomial coefficients of each segment of the fitting datum line and corresponding fitting polynomials, calculating to obtain zero offset values based on the fitting polynomials and the temperature values in the plurality of temperature cycle data files, calculating the mean value, standard deviation and effective value of fitting errors, and generating a text file and a fitting error map. The invention can realize the targeted temperature compensation of the gyroscope in the temperature rising and falling process, and improve the zero offset stability and the effectiveness and reliability of the temperature compensation.
Description
Technical Field
The invention relates to the technical field of temperature compensation of MEMS gyroscopes, in particular to a nonlinear piecewise temperature compensation method of an MEMS gyroscope.
Background
Micro-Electro-Mechanical System (MEMS) gyroscopes mainly consist of a sensitive structure and a signal processing circuit thereof, and are a sensor for measuring the angular velocity of an object by using coriolis force. However, the MEMS gyroscope (hereinafter referred to as gyroscope) is easy to drift in temperature, and the temperature of the external environment and the heat generated during the operation of the gyroscope can change the temperature of the tiny sensitive structure, so that the parameters of the device are changed, and finally the zero drift (hereinafter referred to as zero offset) and the scale factor of the gyroscope are changed. Therefore, gyroscope zero bias and scale factor temperature error compensation is necessary to improve its accuracy.
However, the temperature compensation method in the prior art cannot distinguish the temperature rising and lowering processes to perform the respective temperature compensation, so that the zero offset stability of the gyroscope is poor, and the reliability and the effect of the temperature compensation are poor.
Therefore, there is a need for a temperature compensation method that can distinguish between the temperature rise and temperature fall processes, and temperature compensate the temperature rise data and the temperature fall data, respectively, and improve the zero offset stability and the reliability of the temperature compensation.
Disclosure of Invention
Based on the foregoing, it is necessary to provide a nonlinear piecewise temperature compensation method for a MEMS gyroscope.
A nonlinear piecewise temperature compensation method of a MEMS gyroscope comprises the following steps: acquiring a plurality of temperature cycle data files, determining a data smoothing multiple according to the plurality of temperature cycle data files, and performing data smoothing on the temperature cycle data files according to the data smoothing multiple; identifying a heating process and a cooling process according to the smoothed plurality of temperature tracking data files, and fitting to obtain a fitting datum line, wherein the fitting datum line comprises a heating fitting datum line and a cooling fitting datum line; performing multiple derivatives relative to time according to the discrete data on the fitting datum line, determining the segmentation point number and segmentation point value of the fitting datum line, obtaining fitting orders, fitting each segment of the fitting datum line, obtaining polynomial coefficients of each segment of the fitting datum line, and obtaining corresponding fitting polynomials according to the polynomial coefficients; and calculating zero offset values based on the fitting polynomial and the temperature values in the plurality of temperature cycle data files, calculating the mean value, standard deviation and effective value of fitting errors, and generating a text file and a fitting error map.
In one embodiment, the obtaining a plurality of temperature cycle data files, determining a data smoothing multiple according to the plurality of temperature cycle data files, and performing data smoothing on the temperature cycle data files according to the data smoothing multiple includes: acquiring a plurality of temperature cycle data files, and traversing to obtain the file sizes of the temperature cycle data files; acquiring a data smoothing multiple of a corresponding temperature cycle data file according to the file size; and carrying out smoothing operation on the data in the temperature cycle data file according to the data smoothing multiple to obtain a smoothed temperature cycle data file.
In one embodiment, the identifying a heating process and a cooling process according to the smoothed plurality of temperature cycle data files, and fitting to obtain a fitting reference line includes: acquiring file paths of the smoothed plurality of temperature-tracking data files, identifying a temperature rising process and a temperature lowering process of data in the files according to the smoothed plurality of temperature-tracking data files, and respectively marking correspondingly; according to the temperature data acquisition point, processing the data of the plurality of temperature cycle data files into a new file comprising two temperature cycle data; and acquiring preset weights, and fitting to obtain corresponding fitting datum lines according to the two temperature cycle data combined with the corresponding weights, wherein the fitting datum lines comprise a heating fitting datum line and a cooling fitting datum line.
In one embodiment, the performing derivative with respect to time for multiple times according to the discrete data on the fitting reference line, determining the segmentation point number and the segmentation point value of the fitting reference line, obtaining a fitting order, and performing fitting on each segment of the fitting reference line to obtain a polynomial coefficient and a fitting polynomial of each segment, where the determining includes: obtaining corresponding discrete data according to the fitting datum line, and performing derivative relative to time for a plurality of times according to the discrete data to obtain corresponding segmentation point numbers and segmentation point values; obtaining a fitting order, setting a data column, a temperature output column, temperature rise and fall times and the lowest temperature and the highest temperature of a temperature cycle test, and fitting each section of the fitting datum line by combining the number of the sectional points and the sectional point value to obtain polynomial coefficients of each section of the fitting datum line; and obtaining a corresponding fitting polynomial according to the polynomial coefficient.
In one embodiment, the calculating, based on the fitting polynomial and the temperature values in the plurality of temperature cycle data files, a zero offset value, and calculating a mean value, a standard deviation, and an effective value of a fitting error, generating a text file and a fitting error map includes: according to the fitting polynomial, calculating a corresponding zero offset value by taking temperature values in the plurality of temperature cycle data files as independent variables, wherein the formula is as follows:
y＝b 0 +b 1 T 1 +b 2 T 2 +b 3 T 3 +...b n T n
wherein y is a gyro output value, T is temperature, and n is a fitting order; and calculating the mean value, standard deviation and effective value of the fitting error, and generating a corresponding text file and a fitting error map according to the acquired data.
Compared with the prior art, the invention has the advantages that: the method comprises the steps of obtaining a plurality of temperature cycle files, determining a data smoothing multiple, carrying out data smoothing on the temperature cycle data files according to the data smoothing multiple, identifying a heating process and a cooling process in the smoothed temperature cycle data files, fitting to obtain a corresponding heating fitting datum line and a corresponding cooling fitting datum line, carrying out multiple time derivative relative to time according to discrete data on the fitting datum line, determining the number of segmentation points and segmentation point values of the fitting datum line, obtaining a fitting order, fitting each segment of the fitting datum line to obtain polynomial coefficients of each segment and a corresponding fitting polynomial, calculating to obtain a zero offset value based on the fitting polynomial and temperature values in the temperature cycle data files, thereby realizing targeted temperature compensation of a gyroscope heating process, improving zero offset stability and effectiveness and reliability of temperature compensation, calculating a mean value, a standard deviation and an effective fitting value of fitting errors, generating a text file and an error map, and verifying a temperature compensation result so as to further ensure effectiveness of temperature compensation.
Drawings
FIG. 1 is a flow diagram of a method of nonlinear piecewise temperature compensation of a MEMS gyroscope in one embodiment;
FIG. 2 is a schematic diagram showing the effect of recognizing the temperature rise and fall process after smoothing the temperature cycle data file according to one embodiment;
FIG. 3 is a schematic diagram of a fitting interface setup effect in one embodiment;
FIG. 4 is a schematic diagram of the effect of fitting errors in one embodiment.
Detailed Description
Before proceeding with the description of the embodiments of the present invention, the general inventive concept will be described as follows:
the invention is mainly developed based on the using process of the MEMS gyroscope, the MEMS gyroscope is easy to be influenced by external or self temperature change at present, zero offset is caused, and the accuracy of the measuring result is influenced, but the temperature compensation method in the prior art can not compensate the temperature rising process and the temperature reducing process of the gyroscope respectively, and the compensation effect is poor.
The inventor has found through analysis that the main reason for these problems is that the temperature data measured by the gyroscope is not distinguished by the temperature rise and fall processes, and corresponding temperature compensation is performed based on the temperature rise and fall data, so that the problems can be avoided by distinguishing the temperature rise and fall of the obtained temperature data, and performing temperature compensation respectively. The invention provides a nonlinear piecewise temperature compensation method of an MEMS gyroscope, which comprises the steps of obtaining a plurality of temperature cycle data files obtained by measuring the MEMS gyroscope, determining corresponding smoothing multiples to carry out smoothing treatment on the plurality of temperature cycle data files, identifying a temperature rise and fall process of temperature data based on the smoothed plurality of temperature cycle data files, respectively fitting to obtain a heating fitting datum line and a cooling fitting datum line, carrying out derivative relative to time for a plurality of times according to discrete data on the fitting datum line, thereby determining the piecewise point number and the piecewise point value of the fitting datum line, obtaining fitting order, fitting each section of the fitting datum line, obtaining polynomial coefficients of each section of the fitting datum line and fitting polynomials, calculating to obtain zero offset value based on the temperature values in the fitting polynomials and the plurality of temperature cycle data files, carrying out temperature compensation on the heating or cooling process of the gyroscope based on the zero offset value, ensuring the stability of zero offset and the validity of the temperature compensation, and simultaneously, generating a text file and a fitting error map by calculating the mean value, standard deviation and valid value of fitting error so as to further ensure the reliability of the temperature compensation.
Having described the general inventive concept, the present invention will be further described in detail with reference to the accompanying drawings by way of specific embodiments thereof, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
In one embodiment, as shown in fig. 1, a method for nonlinear piecewise temperature compensation of a MEMS gyroscope is provided, comprising the steps of:
step S101, a plurality of temperature cycle data files are obtained, data smoothing multiples are determined according to the plurality of temperature cycle data files, and the temperature cycle data files are subjected to data smoothing according to the data smoothing multiples.
Specifically, a temperature sensor is arranged in the MEMS gyroscope, a plurality of temperature cycle data files are acquired based on the MEMS gyroscope, and the temperature cycle data files comprise heating data and cooling data; in order to obtain more accurate compensation results according to the plurality of temperature cycle data files, data smoothing multiples can be determined according to the plurality of temperature cycle data files, and data smoothing operation is performed on the corresponding temperature cycle data files according to the data smoothing multiples, so that data accuracy is improved.
The step S101 includes: acquiring a plurality of temperature cycle data files, and traversing to obtain the file sizes of the temperature cycle data files; acquiring a data smoothing multiple of a corresponding temperature cycle data file according to the file size; and carrying out smoothing operation on the data in the temperature cycle data file according to the data smoothing multiple to obtain a smoothed temperature cycle data file.
Specifically, the data in the plurality of temperature cycle data files are read by acquiring file paths of the plurality of temperature cycle data files, and the acquired temperature cycle data files are larger and affected by the performance of computer equipment, so that the file sizes of the temperature cycle data files can be obtained through traversal, and the corresponding data smoothing multiples can be determined, thereby improving the calculation speed. For example, the file size is represented by the number of loading lines of the warm-cycle data file, so that different data smoothing multiples are set according to the number of loading lines, for example, 1000 lines to 5000 lines can set the data smoothing multiple to 5, 5000 lines to 20000 lines can set the data smoothing multiple to 10, and the like.
Step S102, recognizing a heating process and a cooling process according to the smoothed plurality of temperature cycle data files, and fitting to obtain a fitting datum line, wherein the fitting datum line comprises a heating fitting datum line and a cooling fitting datum line.
Specifically, after smoothing operation is performed on the corresponding plurality of temperature cycle data files according to the data smoothing multiple, based on the smoothed data, a heating process and a cooling process in the plurality of temperature cycle data files are identified through collected temperature sensor data, and a corresponding heating fitting datum line and a corresponding cooling fitting datum line are obtained through fitting, so that heating and cooling data in the temperature cycle data files are processed respectively, and accuracy of temperature compensation is ensured.
Wherein, step S102 includes: acquiring file paths of the smoothed plurality of temperature-tracking data files, identifying a temperature rising process and a temperature lowering process of data in the files according to the smoothed plurality of temperature-tracking data files, and respectively marking correspondingly; according to the temperature data acquisition point, processing the data of the plurality of temperature cycle data files into a new file comprising two temperature cycle data; and acquiring preset weights, and fitting to obtain corresponding fitting datum lines according to the combination of the two temperature cycle data and the corresponding weights, wherein the fitting datum lines comprise a heating fitting datum line and a cooling fitting datum line.
Specifically, when the fitting datum line is performed, a temperature rising process and a temperature reducing process of data in the file can be identified by acquiring file paths of the smoothed plurality of data files, corresponding marks are performed respectively, as shown in fig. 2, a black part is the temperature rising process, a gray part is the temperature reducing process, so that data differentiation is performed, the data of the plurality of temperature-cycle data files are processed into a new file comprising two temperature-cycle data according to a temperature data acquisition point, preset weights are acquired, the corresponding fitting datum line is obtained by combining the corresponding weights according to the two temperature-cycle data, and the fitting datum line comprises the temperature-rising fitting datum line and the temperature-reducing fitting datum line. When the weight is set, accumulation of zero offset along with time is considered, for example, the weight of first temperature cycle data is set to be 0.6, and the weight of second temperature cycle data is set to be 0.4, so that two corresponding fitting datum lines for rising and falling are obtained, and are respectively used for temperature compensation in the rising and falling process.
Step S103, performing multiple derivative relative to time according to discrete data on a fitting datum line, determining the segmentation point number and segmentation point value of the fitting datum line, obtaining a fitting order, and fitting each segment of the fitting datum line to obtain polynomial coefficients and fitting polynomials of each segment.
Specifically, a plurality of discrete data are obtained according to a datum line obtained by fitting, derivatives of the discrete data are carried out for a plurality of times relative to time, so that the number of segmentation points and the segmentation point value of the fitting datum line are determined, the fitting order of segmentation temperature compensation is obtained, each segment of the zero offset fitting datum line is fitted, polynomial coefficients of each segment of fitting temperature rise and fall are obtained, and corresponding fitting polynomials are obtained based on the polynomial coefficients.
Wherein, step S103 includes: obtaining corresponding discrete data according to the fitting datum line, and performing multiple time derivative relative to time according to the discrete data to obtain corresponding segmentation point numbers and segmentation point values; obtaining a fitting order, setting a data column, a temperature output column, temperature rise and fall times and the lowest temperature and the highest temperature of a temperature cycle test, and fitting each section of a fitting datum line by combining the number of the sectional points and the sectional point value to obtain polynomial coefficients of each section of the fitting datum line; and obtaining a corresponding fitting polynomial according to the polynomial coefficient.
Specifically, a plurality of corresponding discrete data are obtained according to the fitting datum lines, multiple derivatives relative to time are carried out on the discrete data, the number of the segmentation points and the segmentation point value of the two fitting datum lines are determined based on the obtained results, and the number of the segmentation points can be manually or automatically set.
As shown in fig. 3, the segmentation point number is set to 4, and the segmentation point value comprises a segmentation point 1, a segmentation point 2 and a segmentation point 3, which are respectively-25, 0 and 30; setting the minimum temperature and the maximum temperature of the fitting order, the data column, the temperature output column, the temperature rise and fall times and the temperature cycle test, for example, respectively setting as follows: the fitting order was 4, the data column was 1, the temperature output column was 10, the temperature rise was a make-before-break, the temperature rise was 2 drops, the minimum temperature was set at-40 ℃ and the maximum temperature was set at 60 ℃. The segmentation points may be determined from the third derivative of zero-deviation data with respect to time, or manually entered. Because the fitting datum lines of the temperature rise and fall processes are different, the number of the segmentation points and the segmentation point values are not necessarily the same. In addition, the values of the fitted baseline segmentation points and the segmentation points of different gyroscopes or different data sources are not fixed, but can change according to the transformation of data, and the distances between adjacent segmentation points are also different.
And fitting each section of the fitting datum line by combining the number of the sectional points and the value of the sectional points to obtain polynomial coefficients of each fitting section and corresponding fitting polynomials, and calculating a heating process and a cooling process respectively through the fitting polynomials, so that temperature compensation can be carried out on the heating process respectively, and the accuracy of the temperature compensation is improved.
Step S104, based on the fitting polynomial and the temperature values in the plurality of temperature cycle data files, calculating to obtain a zero offset value, and calculating the mean value, standard deviation and effective value of the fitting error to generate a text file and a fitting error map.
Specifically, based on the obtained fitting polynomials of each section of the temperature rise and fall, the temperature values of the original data files are taken as independent variables, and zero offset values of the temperature rise process and the temperature fall process are calculated respectively, so that the temperature compensation can be carried out on the measured data of the gyroscope according to the zero offset values corresponding to the temperature rise and fall process, and the effectiveness of the temperature compensation and the stability of the zero offset of the gyroscope are ensured; meanwhile, the mean value, standard deviation and effective value of the fitting error can be calculated, and a corresponding text file and fitting error diagram are generated, so that the accuracy of temperature compensation can be judged and verified, and the effectiveness and accuracy of the temperature compensation are further ensured.
When a plurality of temperature cycle data files of the same MEMS gyroscope are imported, the output text file comprises a mean value and standard deviation of multi-time temperature cycle data and piecewise fitting polynomial interpolation and a multi-time temperature cycle data fitting error map.
Wherein, step S104 includes: according to the fitting polynomial, temperature values in a plurality of temperature cycle data files are taken as independent variables, and corresponding zero offset values are calculated, wherein the formula is as follows:
y＝b 0 +b 1 T 1 +b 2 T 2 +b 3 T 3 +...b n T n
wherein y is a gyro output value, T is temperature, and n is a fitting order; and calculating the mean value, standard deviation and effective value of the fitting error, and generating a corresponding text file and a fitting error map according to the acquired data.
Specifically, according to the fitting polynomial and the fitting order, temperature values in a plurality of temperature cycle data files are taken as independent variables, corresponding zero offset values are calculated, and the sectional temperature compensation of the MEMS gyroscope is carried out according to the zero offset values, so that the zero offset stability and the accuracy of the temperature compensation of the gyroscope are improved; meanwhile, the mean value, standard deviation and effective value of the fitting error are calculated, corresponding calculation can be carried out according to an existing formula, a corresponding text file and a fitting error diagram are generated according to the acquired data, wherein the text file comprises the mean value, standard deviation and effective value of multi-time temperature cycle data and piecewise fitting polynomial interpolation and the error diagram of multi-time temperature cycle data fitting, and the effect of temperature compensation can be intuitively displayed through the text file or the fitting error diagram, so that the reliability of temperature compensation can be checked conveniently.
In fig. 4, a fitting error diagram in an embodiment is shown, in the drawing, a Y axis is a gyro output zero offset, an X axis is a temperature value, a solid line is a cooling fitting reference line, a light gray solid line close to the solid line is a cooling fitting compensation curve, a dotted line is a heating fitting reference line, and a light gray dotted line close to the dotted line is a heating fitting compensation curve. It can be seen that the rise and fall Wen Nige compensation curve is relatively close to the rise and fall Wen Nige datum line, which indicates that the temperature compensation effect is better.
In this embodiment, a plurality of temperature cycle files are acquired, a data smoothing multiple is determined, the temperature cycle data files are subjected to data smoothing according to the data smoothing multiple, a heating process and a cooling process in the smoothed plurality of temperature cycle data files are identified, a corresponding heating fitting datum line and a corresponding cooling fitting datum line are obtained through fitting, a derivative of discrete data on the fitting datum line relative to time is carried out for a plurality of times, the number of segmentation points and the segmentation point value of the fitting datum line are determined, a fitting order is acquired, each segment of the fitting datum line is fitted, polynomial coefficients of each segment of the fitting datum line and a corresponding fitting polynomial are obtained, a zero offset value is obtained through calculation based on the fitting polynomial and the temperature values in the plurality of temperature cycle data files, so that targeted temperature compensation of a gyroscope heating process is achieved, stability of zero offset and effectiveness and reliability of temperature compensation are improved, mean value, standard deviation and effective value of fitting errors are calculated, a text file and an error map are generated, so that temperature compensation results are verified, and effectiveness of temperature compensation is further ensured.
Those skilled in the art will appreciate that implementing all or part of the above-described methods in accordance with the embodiments may be accomplished by way of a computer program stored on a computer readable storage medium, which when executed may comprise the steps of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), or the like.
It will be appreciated by those skilled in the art that the modules or steps of the invention described above may be implemented in a general purpose computing device, they may be centralized on a single computing device, or distributed across a network of computing devices, or they may alternatively be implemented in program code executable by computing devices, such that they may be stored on a computer storage medium (ROM/RAM, magnetic or optical disk) for execution by computing devices, and in some cases, the steps shown or described may be performed in a different order than what is shown or described herein, or they may be individually manufactured as individual integrated circuit modules, or a plurality of modules or steps in them may be manufactured as a single integrated circuit module. Therefore, the present invention is not limited to any specific combination of hardware and software.
The foregoing is a further detailed description of the invention in connection with specific embodiments, and is not intended to limit the practice of the invention to such descriptions. It will be apparent to those skilled in the art that several simple deductions or substitutions may be made without departing from the spirit of the invention, and these should be considered to be within the scope of the invention.
Claims (5)
1. The nonlinear piecewise temperature compensation method for the MEMS gyroscope is characterized by comprising the following steps of:
acquiring a plurality of temperature cycle data files, determining a data smoothing multiple according to the plurality of temperature cycle data files, and performing data smoothing on the temperature cycle data files according to the data smoothing multiple;
identifying a heating process and a cooling process according to the smoothed plurality of temperature tracking data files, and fitting to obtain a fitting datum line, wherein the fitting datum line comprises a heating fitting datum line and a cooling fitting datum line;
performing multiple derivatives relative to time according to the discrete data on the fitting datum line, determining the segmentation point number and segmentation point value of the fitting datum line, obtaining fitting orders, and fitting each segment of the fitting datum line to obtain polynomial coefficients and fitting polynomials of each segment;
and calculating zero offset values based on the fitting polynomial and the temperature values in the plurality of temperature cycle data files, calculating the mean value, standard deviation and effective value of fitting errors, and generating a text file and a fitting error map.
2. The method of claim 1, wherein the obtaining a plurality of temperature tracking data files, determining a data smoothing factor according to the plurality of temperature tracking data files, and performing data smoothing on the temperature tracking data files according to the data smoothing factor comprises:
acquiring a plurality of temperature cycle data files, and traversing to obtain the file sizes of the temperature cycle data files;
acquiring a data smoothing multiple of a corresponding temperature cycle data file according to the file size;
and carrying out smoothing operation on the data in the temperature cycle data file according to the data smoothing multiple to obtain a smoothed temperature cycle data file.
3. The method for nonlinear piecewise temperature compensation of a MEMS gyroscope according to claim 1, wherein the steps of identifying a temperature increasing process and a temperature decreasing process from the smoothed plurality of temperature cycle data files and fitting to obtain a fitting reference line comprise:
acquiring file paths of the smoothed plurality of temperature-tracking data files, identifying a temperature rising process and a temperature lowering process of data in the files according to the smoothed plurality of temperature-tracking data files, and respectively marking correspondingly;
according to the temperature data acquisition point, processing the data of the plurality of temperature cycle data files into a new file comprising two temperature cycle data;
and acquiring preset weights, and fitting to obtain corresponding fitting datum lines according to the two temperature cycle data combined with the corresponding weights, wherein the fitting datum lines comprise a heating fitting datum line and a cooling fitting datum line.
4. The method of claim 1, wherein the performing a derivative with respect to time for a plurality of times according to the discrete data on the fitting reference line, determining the number of the segmentation points and the segmentation point value of the fitting reference line, obtaining the fitting order, and performing fitting on each segment of the fitting reference line to obtain a polynomial coefficient and a fitting polynomial of each segment, comprises:
obtaining corresponding discrete data according to the fitting datum line, and performing derivative relative to time for a plurality of times according to the discrete data to obtain corresponding segmentation point numbers and segmentation point values;
obtaining a fitting order, setting a data column, a temperature output column, temperature rise and fall times and the lowest temperature and the highest temperature of a temperature cycle test, and fitting each section of the fitting datum line by combining the number of the sectional points and the sectional point value to obtain polynomial coefficients of each section of the fitting datum line;
and obtaining a corresponding fitting polynomial according to the polynomial coefficient.
5. The method of claim 1, wherein the calculating zero offset based on the fitting polynomial and the temperature values in the plurality of temperature cycle data files, and calculating a mean, standard deviation, and effective value of the fitting error, generating a text file and a fitting error map, comprises:
according to the fitting polynomial, calculating a corresponding zero offset value by taking temperature values in the plurality of temperature cycle data files as independent variables, wherein the formula is as follows:
y＝b 0 +b 1 T 1 +b 2 T 2 +b 3 T 3 +...b n T n
wherein y is a gyro output value, T is temperature, and n is a fitting order;
and calculating the mean value, standard deviation and effective value of the fitting error, and generating a corresponding text file and a fitting error map according to the acquired data.
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| CN117109566A (en) * | 2023-08-23 | 2023-11-24 | 长春航盛艾思科电子有限公司 | IMU temperature compensation method based on piecewise polynomial fitting |
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| CN117109566A (en) * | 2023-08-23 | 2023-11-24 | 长春航盛艾思科电子有限公司 | IMU temperature compensation method based on piecewise polynomial fitting |
| CN117109566B (en) * | 2023-08-23 | 2024-01-23 | 长春航盛艾思科电子有限公司 | IMU temperature compensation method based on piecewise polynomial fitting |
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