CN114280332A - Three-axis acceleration sensor correction method - Google Patents
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Abstract
The invention provides a three-axis acceleration sensor correction method, which comprises the following steps of S1: acquiring a triaxial acceleration data packet of a sensor to be corrected in a static state and data packets of two motion states; s2: constructing a relation between original triaxial data and corrected triaxial data according to the rotation matrix; s3: calculating the current gravity acceleration and the cosine value of an included angle formed by the original triaxial acceleration and the gravity direction; s4: setting constraint conditions, and constructing the relation between the original triaxial acceleration and the cosine of the included angle of the standard X, Y shaft for solving; s5: removing solutions which cannot meet a Cartesian coordinate system through an Euler angle rotation matrix; and finally, verifying the residual solution and outputting a final solution. According to the invention, the correction coefficient of the relational model is calculated and constructed based on the gravity reference calibration and the random motion point data, so that the quick, accurate and efficient correction of the triaxial acceleration sensor is realized.
Description
Technical Field
The invention relates to the technical field of correction of triaxial acceleration sensors, in particular to a correction method of a triaxial acceleration sensor.
Background
The triaxial acceleration sensor is a device for measuring the space acceleration, which is manufactured based on the basic principle of the acceleration, has small volume and light weight, can comprehensively and accurately reflect the motion property of an object, and is widely applied to the fields of aerospace, robots, automobiles, medicine and the like.
In the manufacturing process of the three-axis acceleration sensor, due to factors such as manufacturing process, physical characteristics of manufacturing materials, equipment installation and the like, parameters of different three-axis acceleration sensors are different, and the problem that an obvious included angle exists between the three-axis acceleration sensors and a standard attitude axis generally exists, and the problems can generate huge errors in the analysis, simulation and use process, and finally, abnormal emergency situations encountered in the vehicle motion process cannot be accurately identified.
The current correction method of the triaxial acceleration sensor mainly comprises the following steps: instrumental methods, gravity reference calibration methods, and the like. The instrument method needs external instruments, usually calibration of correction parameters is carried out by means of precise instruments, batch correction calculation of a large number of triaxial acceleration sensors is difficult to carry out in practical application, and the correction calculation of the triaxial acceleration sensors with small user perception is carried out by adopting the method, so that the cost is high; the common gravity reference calibration method has extremely high requirements on sample data, and the sample data is usually obtained in an ideal environment, so that the problems that the sample data obtaining difficulty is high and the batch correction cannot be performed quickly exist in practical application.
Disclosure of Invention
In order to solve the problems, the invention provides a correction method of a triaxial acceleration sensor, which fully utilizes point location data packets generated when the triaxial acceleration sensor normally operates, solves the problem based on gravity reference calibration and correction coefficients of random motion point data through an algorithm of a solving process with low calculation amount, and can quickly, accurately and efficiently correct the sensor without the help of external instruments.
The invention provides a three-axis acceleration sensor correction method, which comprises the following specific technical scheme:
s1: acquiring a triaxial acceleration data packet of a sensor, wherein the triaxial acceleration data packet comprises a data packet of the sensor to be corrected in a static state and two data packets of the sensor to be corrected in a motion state;
s2: constructing a relation between original triaxial data and corrected triaxial data according to the rotation matrix;
s3: calculating the current gravity acceleration and a cosine value of an included angle formed by the original triaxial acceleration and the gravity direction according to the triaxial acceleration data packet in a static state;
s4: setting constraint conditions, constructing the relation between the original triaxial acceleration and the cosine of the included angle of the standard X, Y shaft, and solving according to a triaxial acceleration data packet in a motion state and the cosine value of the included angle formed by the original triaxial acceleration and the gravity direction;
s5: solutions that fail to satisfy the cartesian coordinate system are removed by the euler angle rotation matrix.
Further, in step S4, the constraint condition includes:
in a completely stationary state, the acceleration in the forward direction of the vehicle is zero;
in the completely stationary state, the acceleration in the left direction of the vehicle is zero;
in the motion state, the following conditions are satisfied: the sum of the acceleration vectors of the horizontal plane is the vector difference between the total acceleration of the vehicle and the gravity;
the original three-axis acceleration is vertical to each other;
the corrected standard triaxial accelerations are mutually perpendicular.
Further, after step S5, any one of the solutions satisfying the cartesian coordinate system is acquired as a final correction coefficient.
Further, after step S5, verification is performed according to the forward direction shift direction of the vehicle, and a solution that is correct for the verification is output as a final correction coefficient.
Further, the specific process of the verification is as follows:
collecting a plurality of triaxial acceleration data packets capable of obviously identifying the acceleration and deceleration of the vehicle, and marking the triaxial acceleration data packets to obtain an actual acceleration and deceleration sequence;
inputting the obtained solutions meeting the Cartesian relationship into the relationship between the original triaxial data and the corrected triaxial data, calculating the acceleration of the corrected forward axis x, judging the acceleration and deceleration conditions based on the acceleration, and obtaining the acceleration and deceleration sequence corresponding to each solution;
and calculating the correlation coefficient of the actual acceleration and deceleration sequence and each acceleration and deceleration sequence corresponding to each solution, and outputting the solution corresponding to the sequence with the maximum absolute value of the correlation coefficient and the positive absolute value as the final solution.
Further, the mark specifically includes: and for a plurality of collected triaxial acceleration packets, recording the acceleration as-1 and the deceleration as 1 to obtain the actual acceleration and deceleration sequence containing the marked value and the acceleration and deceleration sequence corresponding to each solution.
The invention has the following beneficial effects:
the method is characterized in that a point location data packet generated when the triaxial acceleration sensor normally operates is utilized, constraint conditions are set based on gravity reference calibration and random motion point data, a relation model of original triaxial acceleration and standard X, Y axial included angle cosine is constructed, a correction coefficient is solved through an algorithm in a solving process with low calculation amount, the algorithm is small in size, high in operation speed, low in cost and high in accuracy, the triaxial acceleration sensor can be quickly, accurately and efficiently corrected in batches without depending on external instruments and harsh experimental environments, and the method is suitable for the triaxial acceleration sensor without obvious distinction among the three axes.
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FIG. 1 is a schematic flow chart of the method of example 1 of the present invention;
FIG. 2 is a schematic flow chart of the method of embodiment 2 of the present invention.
Detailed Description
In the following description, technical solutions in the embodiments of the present invention are clearly and completely described, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
The embodiment 1 of the invention discloses a three-axis acceleration sensor correction method, which is based on a correction coefficient solving algorithm of gravity reference calibration and random motion point data, and the method refers to a gravity reference calibration method, solves nine correction coefficients of an included angle formed by the original three-axis acceleration of a sensor and the three-axis acceleration under a standard posture on the basis of vector summation operation by acquiring three-axis acceleration data packets of a static state and two motion states of the sensor, and screens out correct correction coefficients by calculating a rotation matrix and associating other speed change point data packets.
In the present embodiment, a three-axis acceleration sensor mounted on a vehicle is described as an example;
defining the forward direction of an x axis of the three-axis acceleration sensor obtained through correction as the advancing direction of the vehicle, the forward direction of a y axis as the left direction of the vehicle, and the forward direction of a z axis as the upper part of the vehicle;
the method is suitable for the following conditions:
the original triaxial acceleration and the corrected triaxial acceleration act on the same mass center, namely the corrected standard triaxial acceleration is obtained by rotating the original triaxial acceleration around the mass center;
three output shafts of the three-axis acceleration sensor are mutually vertical in pairs;
the scale factors of all output shafts of the triaxial acceleration sensor are the same;
the posture of the triaxial acceleration sensor is less influenced by environmental factors;
the attitude of the three-axis acceleration sensor is approximately kept constant within a short period (within 30 days).
In practice, the above conditions may be satisfied by the characteristics of the device.
As shown in fig. 1, the specific steps are as follows:
s1: acquiring a triaxial acceleration data packet of a sensor, wherein the triaxial acceleration data packet comprises a data packet of the sensor to be corrected in a static state and two data packets of the sensor to be corrected in a motion state; namely, a triaxial acceleration data packet acquired by a sensor to be corrected in a static state and triaxial acceleration data packets acquired by two different acquisition points in a motion state;
recording the three-axis acceleration in the static state as follows: (static _ acc _ x, static _ acc _ y, static _ acc _ x);
the three-axis accelerations in the two motion states are respectively:
(motion_acc_x_1,motion_acc_y_1,motion_acc_z_1)、
(motion_acc_x_2,motion_acc_y_2,motion_acc_z_2)。
in the embodiment, a triaxial acceleration data packet (-522,675, -478) of the vehicle under the completely static condition is collected; the three-axis acceleration data packets (-567,762, -453) and (-585,731, -622) under any two vehicle motion conditions are collected for illustration.
S2: constructing a relation between original triaxial data and corrected triaxial data according to the rotation matrix;
the rotation rule is defined by a rotation matrix R, which is expressed as follows:
wherein i is a standard triaxial, j is an original triaxial, and values 1-3 represent triaxial x, y and z, cosijExpressing the cosine value of an included angle formed by any two axial directions of the standard three axis and the original three axis; for example, cos12 represents the cosine of the angle that the x-axis in the standard triaxial acceleration data makes with the y-axis in the original triaxial acceleration data.
(x ', y ', z ') represents original triaxial data, and (x, y, z) represents corrected triaxial data, and a relation [ x, y, z ] between the original triaxial data and the corrected triaxial data is constructed]T＝R[x',y',z']The method comprises the following steps:
s3: calculating the current gravity acceleration and a cosine value of an included angle formed by the original triaxial acceleration and the gravity direction according to the triaxial acceleration data packet in a static state;
from the three-axis acceleration data at rest, the current gravitational acceleration grv is calculated by the following formula:
wherein the gravity direction under the standard posture is the negative direction of the z-axis;
taking the data in the above step S1 as an example, it can be found that the current gravitational acceleration is grv — 978.0557 (mg).
The cosine value of the included angle formed by the original triaxial acceleration and the gravity direction is calculated as follows:
taking the data in the step S1 as an example, the included angle between the original triaxial acceleration and the gravitational acceleration is:
s4: setting constraint conditions, constructing the relation between the original triaxial acceleration and the cosine of the included angle of the standard X, Y shaft, and solving according to a triaxial acceleration data packet in a motion state and the cosine value of the included angle formed by the original triaxial acceleration and the gravity direction;
the constraint conditions are as follows:
in a completely stationary state, the acceleration in the forward direction of the vehicle is zero;
in the completely stationary state, the acceleration in the left direction of the vehicle is zero;
in the motion state, the following conditions are satisfied: the sum of the acceleration vectors of the horizontal plane is the vector difference between the total acceleration of the vehicle and the gravity;
the original three-axis acceleration is vertical to each other;
the corrected standard triaxial accelerations are mutually perpendicular.
Based on the constraint conditions and cosine value (cos) of included angle formed by original triaxial acceleration and gravity direction31，cos32，cos33) The relation between the original triaxial acceleration and the cosine of the included angle of the standard X, Y shaft is constructed, and the relation is specifically expressed as follows:
static_acc_x*cos11+static_acc_y*cos12+static_acc_z*cos13＝0
static_acc_x*cos21+static_acc_y*cos22+static_acc_z*cos23＝0
(motion_acc_x_1*cos11+motion_acc_y_1*cos12+motion_acc_z_1*cos13)2+(motion_acc_x_1*cos21+motion_acc_y_1*cos22+motion_acc_z_1*cos23)2
＝motionacc_x_12+motion_acc_y_12+moti。n_acc_z_12-grv2
(motion_acc_x_1*cos11+motion_acc_y_1*cos12+motion_acc_z_1*cos13)2+(motion_acc_x_1*cos21+motion_acc_y_1*cos22+motion_acc_z_1*cos23)2
＝motion_acc_x_12+motion_acc_y_12+motion_acc_z_12-grv2
cos31＝static_acc_x/grv
cos32＝static_acc_y/grv
cos33＝static_acc_z/grv
inputting the constructed relational model into Matlab or Python, and solving;
taking the data in the above step S1 as an example, the results of eight sets of solutions are obtained as follows:
solution 1: [ -0.845665542548865, -0.436360954912043,0.307309139424431, -0.00117259917605077,0.577312198109742,0.816522657937185]
Solution 2: [ -0.845665542548865, -0.436360954912043,0.307309139424431,0.00117259917605077, -0.577312198109742, -0.816522657937185]
Solution 3: [ -0.269187820807410,0.409211416892436,0.871827926493435, -0.801679176461663, -0.596863697457751,0.0326224567552433]
Solution 4: [ -0.269187820807410,0.409211416892436,0.871827926493435,0.801679176461663,0.596863697457751, -0.0326224567552433]
Solution 5: [0.269187820807410, -0.409211416892436, -0.871827926493435, -0.801679176461663, -0.596863697457751,0.0326224567552433]
Solution 6: [0.269187820807410, -0.409211416892436, -0.871827926493435,0.801679176461663,0.596863697457751, -0.0326224567552433]
Solution 7: [0.845665542548865,0.436360954912043, -0.307309139424431, -0.00117259917605077,0.577312198109742,0.816522657937185]
Solution 8: [0.845665542548865,0.436360954912043, -0.307309139424431,0.00117259917605077, -0.577312198109742, -0.816522657937185].
S5: removing solutions which cannot meet a Cartesian coordinate system through an Euler angle rotation matrix;
based on the rotation matrix R, the euler angle rotation matrix is known:
cosine value (cos) of included angle formed by original triaxial acceleration and gravity direction31,cos32,cos33) Substituting into an Euler angle rotation matrix, solving possible values of beta and gamma, wherein two solutions exist respectively:
β＝[acos(cos33),2π-acos(cos33)]
γ＝[atan(cos31/cos32),atan(cos31/cos32)+π]
combining beta and gamma, respectively substituting cos of possible solutions13And cos23From the euler angle rotation matrix, the corresponding sin α and cos α are calculated:
sinα＝cos13/sinβ
cosα＝-cos23/sinβ
then, sin α and cos α are substituted into the Euler angle rotation matrix to solve (cos)11,cos12,cos13,cos21,cos22,cos23) And comparing the solution with the corresponding solution of the rotation matrix R to obtain the same solution (cos)11,cos12,cos13,cos21,cos22,cos23) And (4) through verification, four solutions in the eight solutions meet the Cartesian relationship through verification.
In the practical application process, due to the data acquisition frequency and the complexity of the external environment when the vehicle moves, a triaxial acceleration data packet capable of obviously identifying the acceleration and deceleration of the vehicle cannot be fully acquired; in practical situations, if a sufficient number of triaxial acceleration data packets capable of obviously identifying the acceleration and deceleration of the vehicle cannot be obtained, any one group of solutions can be obtained from the solutions meeting the cartesian coordinate system as the final correction coefficient. Although the forward shaft and the steering shaft cannot be accurately positioned through the correction coefficient, the method still has obvious advantages compared with the method before correction for identifying application scenes such as abnormal conditions under the vehicle running scene.
Example 2
Embodiment 2 of the present invention discloses a method for calibrating a three-axis acceleration sensor, as shown in fig. 2, which includes steps S1-S6, wherein the specific contents of steps S1-S5 are as described in embodiment 1 above, and are not repeated herein.
The same is also illustrated with the data parameters in example 1 above.
In the present embodiment, step S6 is disclosed: verifying according to the speed changing direction of the advancing direction of the vehicle, and outputting a correct verification solution as a final correction coefficient; the method comprises the following specific steps:
acquiring 30 or more triaxial acceleration data packets, obviously identifying the triaxial acceleration data packets under the acceleration and deceleration conditions of the vehicle, marking acceleration or deceleration, marking the acceleration as 1 and the deceleration as-1 to obtain the actual acceleration and deceleration sequence containing the marked value, and marking the actual acceleration and deceleration sequence as forward _ acc _ array;
because factors such as external environment change can affect the sensor, in order to ensure the timeliness of the correction coefficient, sample data (including one completely static state triaxial acceleration data and two motion state triaxial acceleration data) participating in solving is collected as much as possible to obtain the latest data;
inputting the four groups of solutions meeting the Cartesian relationship into the relationship between the original triaxial data and the corrected triaxial data, calculating the acceleration of the corrected advancing axis x, judging the acceleration and deceleration conditions based on the acceleration, wherein the same acceleration mark is 1, the deceleration mark is-1, and the acceleration and deceleration sequence corresponding to each solution is obtained and respectively recorded as: forward _ acc _ array _1, forward _ acc _ array _2, forward _ acc _ array _3, forward _ acc _ array _ 4;
calculating each correlation coefficient of the actual acceleration and deceleration sequence and the acceleration and deceleration sequence corresponding to each solution, and outputting the solution corresponding to the sequence with the largest absolute value and the positive correlation coefficient as the final solution, wherein the correction result is more accurate than that in embodiment 1;
based on the eight solutions in embodiment 1, where solutions 2,3,6, and 7 satisfy the cartesian relationship through verification, in this embodiment, 30 triaxial acceleration data packets are collected as samples, and correlation coefficients of the acceleration and deceleration sequence corresponding to each solution are calculated as: -0.011804, -0.144599, 0.147179, 0.011127, obtaining a final solution of solution 6;
the correction coefficient of the triaxial acceleration sensor can be obtained, namely the rotation matrix R is
By calibration, the triaxial acceleration data packet (-522,675, -478) of the triaxial acceleration sensor under a completely stationary condition will be calibrated to (5.68e-14, -1.07e-14, -978).
The invention is not limited to the foregoing embodiments. The invention extends to any novel feature or any novel combination of features disclosed in this specification and any novel method or process steps or any novel combination of features disclosed.
Claims (6)
1. A three-axis acceleration sensor correction method is characterized by comprising the following steps:
s1: acquiring a triaxial acceleration data packet of a sensor, wherein the triaxial acceleration data packet comprises a data packet of the sensor to be corrected in a static state and two data packets of the sensor to be corrected in a motion state;
s2: constructing a relation between original triaxial data and corrected triaxial data according to the rotation matrix;
s3: calculating the current gravity acceleration and a cosine value of an included angle formed by the original triaxial acceleration and the gravity direction according to the triaxial acceleration data packet in a static state;
s4: setting constraint conditions, constructing the relation between the original triaxial acceleration and the cosine of the included angle of the standard X, Y shaft, and solving according to a triaxial acceleration data packet in a motion state and the cosine value of the included angle formed by the original triaxial acceleration and the gravity direction;
s5: solutions that fail to satisfy the cartesian coordinate system are removed by the euler angle rotation matrix.
2. The three-axis acceleration sensor correction method according to claim 1, characterized in that, in step S4, the constraint conditions include:
in a completely stationary state, the acceleration in the forward direction of the vehicle is zero;
in the completely stationary state, the acceleration in the left direction of the vehicle is zero;
in the motion state, the following conditions are satisfied: the sum of the acceleration vectors of the horizontal plane is the vector difference between the total acceleration of the vehicle and the gravity;
the original three-axis acceleration is vertical to each other;
the corrected standard triaxial accelerations are mutually perpendicular.
3. The triaxial acceleration sensor correcting method of any one of claims 1 to 2, wherein after step S5, any one of solutions satisfying a cartesian coordinate system is acquired as a final correction coefficient.
4. The triaxial acceleration sensor correcting method according to any one of claims 1 to 2, wherein after step S5, verification is performed according to a forward direction shift direction of the vehicle, and a solution that verifies correctness is output as a final correction coefficient.
5. The correction method of the triaxial acceleration sensor according to claim 4, wherein the verification is performed as follows:
collecting a plurality of triaxial acceleration data packets capable of obviously identifying the acceleration and deceleration of the vehicle, and marking the triaxial acceleration data packets to obtain an actual acceleration and deceleration sequence;
inputting the obtained solutions meeting the Cartesian relationship into the relationship between the original triaxial data and the corrected triaxial data, calculating the acceleration of the corrected forward axis x, judging the acceleration and deceleration conditions based on the acceleration, and obtaining the acceleration and deceleration sequence corresponding to each solution;
and calculating the correlation coefficient of the actual acceleration and deceleration sequence and each acceleration and deceleration sequence corresponding to each solution, and outputting the solution corresponding to the sequence with the maximum absolute value of the correlation coefficient and the positive absolute value as the final solution.
6. The three-axis acceleration sensor calibration method according to claim 5, characterized in that the markers are specifically: and for a plurality of collected triaxial acceleration packets, recording the acceleration as-1 and the deceleration as 1 to obtain the actual acceleration and deceleration sequence containing the marked value and the acceleration and deceleration sequence corresponding to each solution.
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| CN116609548A (en) * | 2023-07-20 | 2023-08-18 | 山东省科学院激光研究所 | Three-dimensional optical fiber acceleration sensor system capable of measuring inclination angle |
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