CN114413933B - Dynamic calibration method, system and storage medium for accelerometer - Google Patents
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Abstract
The invention provides a dynamic calibration method of an accelerometer, which comprises the following steps: acquiring a first acceleration of an acceleration count value from the IMU, and acquiring a second acceleration from GNSS data; and (3) performing difference between the first acceleration and the second acceleration to obtain acceleration differences, defining the acceleration differences at K different moments as data, and finally performing polynomial fitting to calibrate the accelerometer. The influence of parameter time variability, equipment installation errors and random errors caused by the environment on the integrated navigation positioning accuracy can be effectively solved, and the factory period and cost of the equipment are effectively shortened.
Description
Technical Field
The invention relates to the field of inertial navigation fusion, in particular to a dynamic calibration method, a dynamic calibration system and a storage medium for an accelerometer.
Background
Currently, the accelerometer calibration of the integrated navigation in the industry mainly adopts a turntable calibration method, for example, the patent with publication numbers of CN110057384A, CN110749750A and CN113295887A, and the method has the advantages of high calibration precision, complex operation, long measurement time of single equipment, expensive turntable equipment with high precision, and great improvement of production cost and product delivery period. In addition, in the conventional method, the installation error of the integrated navigation device which is not assembled before delivery and assembled after delivery cannot be measured. And meanwhile, the influence of random errors caused by later mounting on different devices on the precision of the accelerometer is not considered.
The patent with publication number CN104122412a describes a method for calibrating an accelerometer using the second generation of beidou speed, but has the following drawbacks:
(1) The stability of the system itself cannot be effectively ensured in high real-time.
(2) There is no effective self-assessment scheme for the reliability of calibration results.
(3) The GNSS output speed must reach a certain range to be reliable, and the result is inaccurate in the low-speed condition.
Disclosure of Invention
Based on the above situation, the invention provides a dynamic calibration method and system for an accelerometer, which dynamically calibrates the MEMS accelerometer in real time based on GNSS and wheel speed, can effectively solve the influence of parameter time variability, equipment installation error and random error caused by environment on combined navigation positioning accuracy, and effectively shortens the factory period and cost of the equipment.
The invention discloses a dynamic calibration method of an accelerometer, which comprises the following steps: acquiring a first acceleration a Adding of an acceleration count value from the IMU, and acquiring a second acceleration a gnss from GNSS data; the first acceleration a Adding and the second acceleration a gnss are subjected to difference to obtain an acceleration difference delta a, and K delta a at different moments are defined as a group of data to be stored; when the number k of corresponding acceleration storage array elements is larger than a set threshold k Threshold value and the standard deviation sigma a of the acceleration a in the array is larger than a set threshold sigma a Threshold value , polynomial fitting is carried out to calibrate the accelerometer: polynomial fitting is performed through the k sets of acceleration Δa stored by the device and its corresponding accelerometer output a Adding :
The scale factors and zero bias of the accelerometer for the corresponding acceleration are fitted, where p 0 is zero bias and A 1,p1 is scale factors S 1,p2 through p q are small amounts of high order error.
The method for dynamically calibrating an accelerometer according to claim 1, wherein when the number k of the corresponding acceleration storage array elements is greater than a set threshold k Threshold value and the standard deviation σ a of the acceleration a in the array is smaller than the set threshold σ a Threshold value , calibrating the accelerometer by using a mean; the mean value A 2 of the acceleration difference delta a between the k groups of GNSS calculated accelerations stored by the computing equipment and the accelerometer is calibrated as zero offset of the accelerometer
When the absolute value of the difference between the zero polarization A 1 and the estimated addition zero polarization A Estimation is smaller than a preset threshold A Threshold value , the accelerometer adopts a polynomial fitting function to calibrate the scale factor and the zero polarization; and when the absolute value of the difference between the average value A 2 of the acceleration difference delta a and the estimated addition zero offset A Estimation is smaller than a preset threshold value A Threshold value , the accelerometer adopts the average value A 2 of the acceleration difference delta a as the zero offset of the accelerometer for calibration.
And after the first zero offset calibration is successful, the system stores the difference between the n groups of calibrated accelerometer outputs and GNSS calculated accelerations, calculates the standard deviation of the difference between the n groups of calibrated accelerometer outputs and the GNSS calculated accelerations, and stores the standard deviation as sigma 1. When the accelerometer scale factors and zero offset calibration results which meet the condition of the step S4 are completed for the second time, the system continues to use the first scale factors and zero offset calibration results, but n groups of accelerometer outputs corrected by the second scale factors and the zero offset calibration results are calculated in parallel, and the standard deviation of the difference between the accelerometer outputs corrected by the second scale factors and the zero offset calibration results and the GNSS calculated acceleration is stored as sigma 2. And comparing sigma 1 with sigma 2, and selecting a group of updated calibration results with smaller standard deviation values.
When the acquired GNSS speed V GNSS is continuously larger than the set speed threshold V Threshold value ; the speed values in the GNSS data are available; when the acquired GNSS speed V GNSS is continuously greater than or equal to the set speed threshold V Threshold value ; the fusion speed of the GNSS and the wheel speed meter is calculated through the acquired GNSS speed V GNSS and the wheel speed meter speed V Wheel :
V Melting and melting ＝ωGNSSVGNSS+ω Wheel V Wheel
ω GNSS is the GNSS speed weight ω Wheel is the wheel speed weight. Both conform to the formula:
1＝ωGNSS+ω Wheel
as V Wheel increases, ω Wheel decreases, with the relationship as follows, where k is the weight correction factor:
The invention also provides a dynamic calibration system of the accelerometer, which is characterized by comprising an IMU data module, a GNSS data module and a dynamic calibration data module, wherein the modules are in data connection; the IMU data module is used for acquiring a first acceleration a Adding of the acceleration count value;
The GNSS data module is used for the second acceleration a gnss; the dynamic calibration data module respectively acquires the first acceleration a Adding and the second acceleration a gnss, makes a difference between the first acceleration a Adding and the second acceleration a gnss to obtain an acceleration difference delta a, and defines the delta a at K different moments as a group of data to store; when the number k of corresponding acceleration storage array elements is larger than a set threshold k Threshold value and the standard deviation sigma a of the acceleration a in the array is larger than a set threshold sigma a Threshold value , polynomial fitting is carried out to calibrate the accelerometer: polynomial fitting is performed through the k sets of acceleration Δa stored by the device and its corresponding accelerometer output a Adding :
The scale factors and zero bias of the accelerometer for the corresponding acceleration are fitted, where p 0 is zero bias and A 1,p1 is scale factors S 1,p2 through p q are small amounts of high order error.
When the number k of corresponding acceleration storage array elements is larger than a set threshold k Threshold value and the standard deviation sigma a of the acceleration a in the array is smaller than a set threshold sigma a Threshold value , calibrating the accelerometer by adopting a mean value; the mean value A 2 of the acceleration difference delta a between the k groups of GNSS calculated accelerations stored by the computing equipment and the accelerometer is calibrated as zero offset of the accelerometer
Compared with the prior art, the method is simple to operate, the first acceleration of the acceleration count value is obtained from the IMU, the second acceleration is obtained from the GNSS data, the real-time dynamic calibration is carried out, and the effective fitting can be carried out according to an algorithm. The influence of parameter time variability, equipment installation error and random error caused by environment on the integrated navigation positioning precision can be effectively solved, and the factory period and cost of the equipment are effectively shortened.
Drawings
FIG. 1 is a flow chart of a method for dynamically calibrating an accelerometer according to the present invention;
FIG. 2 is a schematic diagram of an embodiment of an accelerometer dynamic alignment system according to the present invention.
Detailed Description
The present invention will be described in detail with reference to preferred embodiments thereof.
As shown in fig. 1, the method in this embodiment includes the steps of:
S1, acquiring a first acceleration a Adding of an acceleration count value from an IMU and acquiring a second acceleration a gnss from GNSS data; the first acceleration a Adding and the second acceleration a gnss are subjected to difference to obtain an acceleration difference delta a, and the delta a at K different moments is defined as a group of data to be stored.
By collecting GNSS, IMU and wheel speed meter data: and installing the integrated navigation equipment in the mobile test equipment, starting the equipment to move and collecting GNSS, IMU and wheel speed meter output data, wherein the wheel speed meter is arranged to solve the problem of inaccurate positioning of the GNSS under the condition of low speed.
Before using IMU data, the IMU stability needs to be judged. When the time t 1 of acquiring the data of the continuously available GNSS is greater than or equal to the time threshold t 1 Threshold value , standard deviations of the X-axis, Y-axis and Z-axis outputs of the IMU gyroscope in the time t are calculated. When standard deviations sigma x and sigma y of the X-axis and Y-axis output of the IMU gyroscope are respectively smaller than set threshold values sigma x Threshold value and sigma t Threshold value , judging that the horizontal direction of the equipment is stable; and when the standard deviation sigma z of the Z-axis measurement output of the IMU gyroscope is smaller than the set threshold sigma x Threshold value , judging that the data heading is stable. At this time, the IMU acquires the first acceleration a Adding of the acceleration count value.
When judging by using GNSS and wheel speed data: when the GNSS solution type is a fixed solution or a floating solution, the acquired GNSS signals are available; when the acquired GNSS speed V GNSS is continuously greater than the set speed threshold V Threshold value , the acquired GNSS speed is available; when the acquired GNSS navigation is forward and backward epoch differenceCombined heading change with IMU gyroscope Z-axis solution over the period of timeThe difference between them is less than the heading difference thresholdWhen the navigation system is used, the navigation acquired by the GNSS is available; and when all the conditions are met, judging that the acquired GNSS data is available. When the collected wheel speed V Wheel is continuously greater than the set speed threshold V Wheel threshold , the collected wheel speed data is judged to be available.
Fusion of speeds acquired by GNSS and wheel speed meters: the fusion speed of the GNSS and the wheel speed meter is calculated through the acquired GNSS speed V GNSS and the wheel speed meter speed V Wheel :
V Melting and melting ＝ωGNSSVGNSS+ω Wheel V Wheel
ω GNSS is the GNSS speed weight ω Wheel is the wheel speed weight. Both conform to the formula:
1＝ωGNSS+ω Wheel
as V Wheel increases, ω Wheel decreases, with the relationship as follows, where k is the weight correction factor:
After the calculation, the second acceleration a gnss is obtained from the GNSS data, which is a value that is more suitable for the actual situation.
If the GNSS data are available and the IMU device determines that the data are stable, the acceleration of the available GNSS data in the time t is calculated and is differenced from the time output corresponding to the accelerometer, the acceleration a GNSS calculated by the data of each GNSS and the corresponding accelerometer output first acceleration a Adding , and the acceleration difference Δa between a GNSS and a Adding are defined as a set of data to be stored.
S2, when the number k of corresponding acceleration storage array elements is larger than a set threshold k Threshold value , and the standard deviation sigma a of the acceleration a in the array is larger than a set threshold sigma a Threshold value , polynomial fitting is carried out to calibrate the accelerometer: the fitting polynomial is obtained from the k sets of accelerations Δa stored by the device and their corresponding accelerometer outputs a Adding :
The scale factors and zero offset of the accelerometer for the corresponding acceleration are fitted, where p 0 is zero offset A 1,p1 is the scale factors S 1,p2 through p q are small amounts of high order error.
S3, when the number k of corresponding acceleration storage array elements is larger than a set threshold k Threshold value , and the standard deviation sigma a of the acceleration a in the array is smaller than the set threshold sigma a Threshold value , calibrating the accelerometer by adopting a mean value; the mean value A 2 of the acceleration difference delta a between the k groups of GNSS calculated accelerations stored by the computing equipment and the accelerometer is calibrated as zero offset of the accelerometer
S4, correcting accelerometer parameters: when the step S2 is completed and the absolute value of the difference between the A 1 and the estimated addition zero offset A Estimation is smaller than a preset threshold A Threshold value , the accelerometer adopts a polynomial fitting function to calibrate the scale factor and the zero offset; when step S3 is completed and the absolute value of the difference between a 2 and the pre-estimated addition zero offset a Estimation is less than the preset threshold a Threshold value , the accelerometer adopts a 2 as the accelerometer zero offset for calibration. If the absolute values of the differences between A 1 or A 2 and the estimated accelerometer zero offset are both greater than the threshold A Threshold value , the accelerometer zero offset and the scale factor are not updated, and the system returns to the loop scale procedure of step S1. In case of successful non-first calibration, the calibration result is not updated directly, but is judged by step S5.
S5: and (3) fusion positioning and correction effect judgment: and after the first zero offset calibration is successful, the system stores the difference between the n groups of calibrated accelerometer outputs and GNSS calculated accelerations, calculates the standard deviation of the difference between the n groups of calibrated accelerometer outputs and the GNSS calculated accelerations, and stores the standard deviation as sigma 1. When the accelerometer scale factors and zero offset calibration results which meet the condition of the step S4 are completed for the second time, the system continues to use the first scale factors and zero offset calibration results, but n groups of accelerometer outputs corrected by the second scale factors and the zero offset calibration results are calculated in parallel, and the standard deviation of the difference between the accelerometer outputs corrected by the second scale factors and the zero offset calibration results and the GNSS calculated acceleration is stored as sigma 2. And comparing sigma 1 with sigma 2, selecting a group of updated calibration results with smaller standard deviation values, and verifying the subsequent calibration results conforming to the condition of the step S4 by adopting the same method.
It should be noted that: the foregoing "first and second …" do not represent a specific number or order, but merely serve to distinguish between names.
A schematic structural diagram of an embodiment of an accelerometer dynamic alignment system according to the present invention is shown in fig. 2, which includes: the system comprises an IMU data module, a GNSS data module and a dynamic calibration data module, wherein the modules are in data connection; the IMU data module is used for acquiring a first acceleration a Adding of the acceleration count value;
The GNSS data module is used for the second acceleration a gnss; the dynamic calibration data module respectively acquires the first acceleration a Adding and the second acceleration a gnss, makes a difference between the first acceleration a Adding and the second acceleration a gnss to obtain an acceleration difference delta a, and defines the delta a at K different moments as a group of data to store; when the number k of corresponding acceleration storage array elements is larger than a set threshold k Threshold value and the standard deviation sigma a of the acceleration a in the array is larger than a set threshold sigma a Threshold value , polynomial fitting is carried out to calibrate the accelerometer: the fitting polynomial is obtained from the k sets of accelerations Δa stored by the device and their corresponding accelerometer outputs a Adding :
The scale factors and zero offset of the accelerometer for the corresponding acceleration are fitted, where p 0 is zero offset A 1,p1 is the scale factors S 1,p2 through p q are small amounts of high order error.
When the number k of corresponding acceleration storage array elements is larger than a set threshold k Threshold value and the standard deviation sigma a of the acceleration a in the array is smaller than a set threshold sigma a Threshold value , calibrating the accelerometer by adopting a mean value; the mean value A 2 of the acceleration difference delta a between the k groups of GNSS calculated accelerations stored by the computing equipment and the accelerometer is calibrated as zero offset of the accelerometer
When the absolute value of the difference between the zero offset A 1 and the pre-estimated zero offset A Estimation is smaller than a preset threshold A Threshold value , the accelerometer adopts a polynomial fitting function to calibrate the scale factor and the zero offset; and when the absolute value of the difference between the average value A 2 of the acceleration difference delta a and the estimated addition zero offset A Estimation is smaller than a preset threshold value A Threshold value , the accelerometer adopts the average value A 2 of the acceleration difference delta a as the zero offset of the accelerometer for calibration. When the acquired GNSS speed V GNSS is continuously larger than the set speed threshold V Threshold value ; the speed values in the GNSS data are available; when the acquired GNSS speed V GNSS is continuously greater than or equal to the set speed threshold V Threshold value ; the fusion speed of the GNSS and the wheel speed meter is calculated through the acquired GNSS speed V GNSS and the wheel speed meter speed V Wheel :
V Melting and melting ＝ωGNSSVGNSS+ω Wheel V Wheel
ω GNSS is the GNSS speed weight ω Wheel is the wheel speed weight. Both conform to the formula:
1＝ωGNSS+ω Wheel
as V Wheel increases, ω Wheel decreases, with the relationship as follows, where k is the weight correction factor:
Finally, the invention also provides a computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, implements the steps of the above method.
The foregoing examples merely illustrate embodiments of the invention and are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
Claims (10)
1. A method of dynamically calibrating an accelerometer, comprising the steps of: acquiring a first acceleration a Adding of an acceleration count value from the IMU, and acquiring a second acceleration a gnss from GNSS data; the first acceleration a Adding and the second acceleration a gnss are subjected to difference to obtain an acceleration difference delta a, and K delta a at different moments are defined as a group of data to be stored; when the number k of corresponding acceleration storage array elements is larger than a set threshold k Threshold value and the standard deviation sigma a of the acceleration a in the array is larger than a set threshold sigma a Threshold value , polynomial fitting is carried out to calibrate the accelerometer: the fitting polynomial is obtained from the k sets of accelerations Δa stored by the device and their corresponding accelerometer outputs a Adding :
The scale factors and zero offset of the accelerometer for the corresponding acceleration are fitted, where p 0 is zero offset A 1,p1 is the scale factors S 1,p2 through p q are small amounts of high order error.
2. The method for dynamically calibrating an accelerometer according to claim 1, wherein when the number k of the corresponding acceleration storage array elements is greater than a set threshold k Threshold value and the standard deviation σ a of the acceleration a in the array is smaller than the set threshold σ a Threshold value , calibrating the accelerometer by using a mean; the mean value A 2 of the acceleration difference delta a between the k groups of GNSS calculated accelerations stored by the computing equipment and the accelerometer is calibrated as zero offset of the accelerometer
3. The method according to claim 2, wherein the accelerometer uses a polynomial fitting function to calibrate the scale factor and zero offset when the absolute value of the difference between the zero offset value a 1 and the pre-estimated zero offset value a Estimation is smaller than a preset threshold value a Threshold value ; and when the absolute value of the difference between the average value A 2 of the acceleration difference delta a and the estimated addition zero offset A Estimation is smaller than a preset threshold value A Threshold value , the accelerometer adopts the average value A 2 of the acceleration difference delta a as the zero offset of the accelerometer for calibration.
4. The method of claim 3, wherein after the first zero offset calibration is successful, the system stores the differences between the n sets of calibrated accelerometer outputs and the GNSS calculated accelerations, and calculates the standard deviation of the differences therebetween to store as σ 1; when the accelerometer scale factors and zero offset calibration results which meet the condition of the step S4 appear for the second time, the system continues to use the first scale factors and zero offset calibration results, but simultaneously calculates n groups of standard deviations of differences between accelerometer output corrected by the second scale factors and the zero offset calibration results and GNSS calculated acceleration in parallel and stores the standard deviations as sigma 2; and comparing sigma 1 with sigma 2, and selecting a group of updated calibration results with smaller standard deviation values.
5. The method of dynamic calibration of an accelerometer according to any one of claims 1 to 4, wherein when the acquired GNSS speed V GNSS is continuously greater than the set speed threshold V Threshold value ; the speed values in the GNSS data are available; when the acquired GNSS speed V GNSS is continuously greater than or equal to the set speed threshold V Threshold value ; calculating the fusion speed of the GNSS and the wheel speed meter through the acquired GNSS speed V GNSS and the acquired wheel speed V Wheel ;
V Melting and melting ＝ωGNSSVGNSS+ω Wheel V Wheel
ω GNSS is a GNSS speed weight ω Wheel is a wheel speed weight, both of which conform to the formula:
1＝ωGNSS+ω Wheel
as V Wheel increases, ω Wheel decreases, with the relationship as follows, where k is the weight correction factor:
6. The accelerometer dynamic calibration system is characterized by comprising an IMU data module, a GNSS data module and a dynamic calibration data module, wherein the modules are in data connection; the IMU data module is used for acquiring a first acceleration a Adding of the acceleration count value;
The GNSS data module is used for second acceleration a gnss; the dynamic calibration data module respectively acquires the first acceleration a Adding and the second acceleration a gnss, makes a difference between the first acceleration a Adding and the second acceleration a gnss to obtain an acceleration difference delta a, and defines the delta a at K different moments as a group of data to store; when the number k of corresponding acceleration storage array elements is larger than a set threshold k Threshold value and the standard deviation sigma a of the acceleration a in the array is larger than a set threshold sigma a Threshold value , polynomial fitting is carried out to calibrate the accelerometer: the fitting polynomial is obtained from the k sets of accelerations Δa stored by the device and their corresponding accelerometer outputs a Adding :
The scale factors and zero offset of the accelerometer for the corresponding acceleration are fitted, where p 0 is zero offset A 1,p1 is the scale factors S 1,p2 through p q are small amounts of high order error.
7. The dynamic calibration system of claim 6, wherein when the number k of elements in the corresponding acceleration storage array is greater than a set threshold k Threshold value and the standard deviation σ a of the acceleration a in the array is less than a set threshold σ a Threshold value , calibrating the accelerometer with a mean; the mean value A 2 of the acceleration difference delta a between the k groups of GNSS calculated accelerations stored by the computing equipment and the accelerometer is calibrated as zero offset of the accelerometer
8. The dynamic alignment system of claim 6 wherein the accelerometer uses a polynomial fit function to calibrate the scale factor and zero offset when the absolute value of the difference between the zero offset value a 1 and the pre-estimated zero offset a Estimation is less than a preset threshold a Threshold value ; and when the absolute value of the difference between the average value A 2 of the acceleration difference delta a and the estimated addition zero offset A Estimation is smaller than a preset threshold value A Threshold value , the accelerometer adopts the average value A 2 of the acceleration difference delta a as the zero offset of the accelerometer for calibration.
9. The accelerometer dynamic alignment system according to any of claims 6-8 wherein when the acquired GNSS speed V GNSS is continuously greater than the set speed threshold V Threshold value ; the speed values in the GNSS data are available; when the acquired GNSS speed V GNSS is continuously greater than or equal to the set speed threshold V Threshold value ; the fusion speed of the GNSS and the wheel speed meter is calculated through the acquired GNSS speed V GNSS and the wheel speed meter speed V Wheel :
V Melting and melting ＝ωGNSSVGNSS+ω Wheel V Wheel
ω GNSS is a GNSS speed weight ω Wheel is a wheel speed weight, both of which conform to the formula:
1＝ωGNSS+ω Wheel
as V Wheel increases, ω Wheel decreases, with the relationship as follows, where k is the weight correction factor:
10. a computer readable storage medium having stored thereon a computer program characterized by: the computer program, when executed by a processor, implements the steps of the method of any of claims 1 to 5.
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| CN102662083A (en) * | 2012-03-28 | 2012-09-12 | 北京航空航天大学 | Accelerometer calibration method based on GPS velocity information |
| CN109827593A (en) * | 2018-09-11 | 2019-05-31 | 广东星舆科技有限公司 | A kind of error self-calibrating method, system and storage medium based on more IMU |
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| CN109827593A (en) * | 2018-09-11 | 2019-05-31 | 广东星舆科技有限公司 | A kind of error self-calibrating method, system and storage medium based on more IMU |
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