CN114280332B - Triaxial acceleration sensor correction method - Google Patents
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Abstract
The invention provides a triaxial 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 the sensor to be corrected in two motion states; s2: constructing a relation between the original triaxial data and the corrected triaxial data according to the rotation matrix; s3: calculating cosine values of the included angles formed by the current gravity acceleration and the original triaxial acceleration and the gravity direction; s4: setting constraint conditions, and constructing relations between the original triaxial acceleration and the standard X, Y axial clamp angle cosine respectively for solving; s5: removing solutions which fail to meet a Cartesian coordinate system through the Euler angle rotation matrix; and finally, verifying the residual solution and outputting a final solution. According to the method, the correction coefficient of the relation model is constructed based on gravity reference calibration and random motion point position data calculation, so that the triaxial acceleration sensor is corrected rapidly, accurately and efficiently.
Description
Technical Field
The invention relates to the technical field of triaxial acceleration sensor correction, in particular to a triaxial acceleration sensor correction method.
Background
The triaxial acceleration sensor is a device for measuring the spatial acceleration, which is manufactured based on the basic principle of 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 of the triaxial acceleration sensor, the parameters of the triaxial acceleration sensor are different due to factors such as manufacturing process, physical characteristics of manufacturing materials, equipment installation and the like, and the problems that an obvious included angle is formed between the triaxial acceleration sensor and a standard attitude axis are common, and huge errors can be generated in the process of analysis and simulation use, so that abnormal emergency situations encountered in the process of vehicle movement can not be accurately identified finally.
The correction method of the existing triaxial acceleration sensor mainly comprises the following steps: an instrument method, a gravity reference calibration method and the like. The method is difficult to perform batch correction calculation on a large number of triaxial acceleration sensors in practical application, and the method is used for performing correction calculation on the triaxial acceleration sensor with smaller perception of a user and has higher cost; the common gravity reference calibration method has extremely high requirements on sample data, is usually sample data acquired in an ideal environment, and has the problems that the sample data acquisition difficulty is high and quick batch correction cannot be realized in practical application.
Disclosure of Invention
In order to solve the problems, the invention provides a three-axis acceleration sensor correction method, which fully utilizes point location data packets generated during normal operation of the three-axis acceleration sensor, solves the problem by using a low-calculation-amount algorithm based on gravity reference calibration and correction coefficients of random motion point location data, and can quickly, accurately and efficiently correct the sensor without using an external instrument.
The invention provides a triaxial 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 in a static state and data packets in two motion states of the sensor to be corrected;
S2: constructing a relation between the original triaxial data and the corrected triaxial data according to the rotation matrix;
S3: according to the triaxial acceleration data packet in the static state, 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, constructing relations between original triaxial acceleration and cosine of a standard X, Y axis clamp angle respectively, and solving according to triaxial acceleration data packets in a motion state and cosine values of included angles formed by the original triaxial acceleration and a 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 the completely stationary state, the acceleration in the vehicle forward direction is zero;
in the completely stationary state, the acceleration in the left direction of the vehicle is zero;
under the motion state, satisfy: acceleration vector sum of horizontal plane = vector difference of vehicle overall acceleration and gravity;
the original triaxial accelerations are mutually perpendicular;
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 the final correction coefficient.
Further, after step S5, the vehicle is verified according to the forward direction shift direction, and a solution for verifying the correctness is outputted as a final correction coefficient.
Further, the specific process of verification is as follows:
Collecting a plurality of triaxial acceleration data packets capable of obviously identifying the acceleration and deceleration conditions 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 advancing axis x, and judging acceleration and deceleration conditions based on the acceleration to obtain an acceleration and deceleration sequence corresponding to each solution;
And 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 maximum absolute value of the correlation coefficient and positive value as a final solution.
Further, the marking specifically includes: and for a plurality of collected triaxial acceleration packages, the acceleration is marked as-1, the deceleration is marked as 1, and the actual acceleration and deceleration sequence containing the marking value and the acceleration and deceleration sequence corresponding to each solution are obtained.
The beneficial effects of the invention are as follows:
The method is characterized in that a point data packet generated during normal operation of the triaxial acceleration sensor 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 shaft clamping angle cosine is constructed, a correction coefficient is solved through an algorithm of a solving process with low calculation amount, the algorithm is small in volume, high in operation speed, low in cost and high in accuracy, the triaxial acceleration sensor can be corrected rapidly, accurately and efficiently in batches under the condition of not depending on an external instrument and a harsh experimental environment, and the method is suitable for triaxial acceleration sensors without obvious distinction between triaxial.
Drawings
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, the technical solutions of the embodiments of the present invention are clearly and completely described, and it is obvious that the described embodiments are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
The embodiment 1 of the invention discloses a correction method of a triaxial acceleration sensor, which is based on a correction coefficient solving algorithm of gravity reference calibration and random motion point position data.
In the present embodiment, a three-axis acceleration sensor mounted on a vehicle will be described as an example;
Defining the forward direction of the X-axis of the three-axis acceleration sensor obtained through correction as the forward direction of the vehicle, the forward direction of the Y-axis as the left direction of the vehicle and the forward direction of the Z-axis as the upper direction of the vehicle;
And 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 triaxial acceleration sensor are mutually perpendicular;
the scale factors of the output shafts of the triaxial acceleration sensor are the same;
the posture of the triaxial acceleration sensor is less influenced by environmental factors;
the three-axis acceleration sensor pose remains unchanged with a high probability 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 step flow is as follows:
S1: acquiring a triaxial acceleration data packet of a sensor, wherein the triaxial acceleration data packet comprises a data packet in a static state and data packets in two motion states of the sensor to be corrected; the sensor to be corrected is in a static state, one triaxial acceleration data packet is collected, and in a motion state, triaxial acceleration data packets are collected at two different collection points;
The triaxial acceleration in the static state is recorded as follows: (static_acc_x, static_acc_y, static_acc_x);
The triaxial acceleration under two motion states is 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 this embodiment, three-axis acceleration data packets (-522,675, -478) of the vehicle under the condition of complete standstill are acquired; three-axis acceleration data packets (-567,762, -453) and (-585,731, -622) under any two vehicle motion conditions are taken as examples for illustration.
S2: constructing a relation between the original triaxial data and the 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, values 1-3 respectively represent x, y and z triaxial, and cos ij is a cosine value of an included angle formed by any two axial directions of the standard triaxial and the original triaxial; for example, cos12 represents the cosine of the angle between the x-axis in the standard triaxial acceleration data and the y-axis in the original triaxial acceleration data.
The notation (x ', y', z ') denotes the original triaxial data and (x, y, z) denotes the corrected triaxial data, and the relationship [ x, y, z ] T =r [ x', y ', z' ] between the original triaxial data and the corrected triaxial data is constructed as follows:
S3: according to the triaxial acceleration data packet in the static state, calculating the current gravity acceleration and the cosine value of an included angle formed by the original triaxial acceleration and the gravity direction;
according to the triaxial acceleration data in the static state, the current gravitational acceleration grv is calculated according to the following formula:
Wherein the gravity direction is negative direction of the z axis under the standard posture;
Taking the data in step S1 as an example, the current gravitational acceleration may be 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 above step S1 as an example, the included angle between the original triaxial acceleration and the gravitational acceleration is:
S4: setting constraint conditions, constructing relations between original triaxial acceleration and cosine of a standard X, Y axis clamp angle respectively, and solving according to triaxial acceleration data packets in a motion state and cosine values of included angles formed by the original triaxial acceleration and a gravity direction;
The constraint conditions are as follows:
in the completely stationary state, the acceleration in the vehicle forward direction is zero;
in the completely stationary state, the acceleration in the left direction of the vehicle is zero;
under the motion state, satisfy: acceleration vector sum of horizontal plane = vector difference of vehicle overall acceleration and gravity;
the original triaxial accelerations are mutually perpendicular;
The corrected standard triaxial accelerations are mutually perpendicular.
Based on the constraint conditions and cosine values (cos 31,cos32,cos33) of included angles formed by the original triaxial acceleration and the gravity direction, a relation between the original triaxial acceleration and the cosine of the standard X, Y axis clamp angle is constructed, and the relation is specifically shown 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 relation model into Matlab or Python for solving;
taking the data in step S1 as an example, 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 fail to meet a Cartesian coordinate system through the Euler angle rotation matrix;
Based on the rotation matrix R, the euler angle rotation matrix is known:
Substituting cosine values (cos 31,cos32,cos33) of included angles formed by the original triaxial acceleration and the gravity direction into Euler angle rotation matrixes, and 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, substituting cos 13 and cos 23 which are possibly solved respectively, and calculating corresponding sin alpha and cos alpha through Euler angle rotation matrixes:
sinα＝cos13/sinβ
cosα＝-cos23/sinβ
And then sin alpha and cos alpha are substituted into the Euler angle rotation matrix, the solution (cos 11,cos12,cos13,cos21,cos22,cos23) is solved, and the solution of the same solution (cos 11,cos12,cos13,cos21,cos22,cos23) can be solved by comparing the solution with the solution corresponding to the rotation matrix R, and through verification, four solutions in eight groups of solutions satisfy the Cartesian relationship through verification.
In the actual application process, due to the data acquisition frequency and the complexity of the external environment when the vehicle moves, the triaxial acceleration data packet capable of obviously identifying the acceleration and deceleration of the vehicle may not be fully acquired; in actual situations, if a sufficient amount of triaxial acceleration data packets capable of obviously identifying the acceleration and deceleration of the vehicle cannot be obtained, any one set of solutions can be obtained from solutions meeting a cartesian coordinate system as final correction coefficients. Although the forward shaft and the steering shaft cannot be accurately positioned through the correction coefficient, the correction coefficient has obvious advantages for identifying application scenes such as abnormal situations in a vehicle running scene and the like before correction.
Example 2
Embodiment 2 of the present invention discloses a method for correcting a triaxial acceleration sensor, as shown in fig. 2, including steps S1-S6, wherein specific contents of steps S1-S5 are described in embodiment 1 above, and detailed description thereof is omitted herein.
The same description will be made with respect to the data parameters in the above-described embodiment 1.
In this embodiment, step S6 is disclosed: verifying according to the speed change direction of the vehicle, and outputting a correct verification solution as a final correction coefficient; the method comprises the following steps:
collecting 30 or more triaxial acceleration data packets capable of obviously identifying acceleration and deceleration conditions of a vehicle, marking acceleration or deceleration, marking the acceleration as 1, marking the deceleration as-1, and obtaining the actual acceleration and deceleration sequence containing a marking value as forward_acc_array;
Because factors such as external environment change can influence the sensor, in order to ensure the timeliness of the correction coefficient, sample data (comprising one complete static state triaxial acceleration data and two motion state triaxial acceleration data) participating in solving are acquired as much as possible to acquire the latest data;
Inputting the obtained 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, and obtaining acceleration and deceleration sequences corresponding to each solution by marking the same acceleration as 1 and the same deceleration as-1, wherein the acceleration and deceleration sequences are respectively recorded as follows: 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 a solution corresponding to the sequence with the largest absolute value of the correlation coefficient and positive value as a final solution, wherein compared with the embodiment 1, the correction result is more accurate;
Based on the above eight solutions in embodiment 1, where solutions 2,3,6, and 7 satisfy the cartesian relationship through verification, 30 triaxial acceleration data packets are collected as samples in this embodiment, and correlation coefficients of acceleration and deceleration sequences corresponding to each solution are calculated as follows: -0.011804, -0.144599,0.147179,0.011127 to obtain a final solution of solution 6;
The correction coefficient of the triaxial acceleration sensor can be obtained, namely the rotation matrix R is
By correction, the tri-axis acceleration sensor in the fully stationary case tri-axis acceleration data packet (-522,675, -478) will be corrected to (5.68 e-14, -1.07e-14, -978).
The invention is not limited to the specific embodiments described above. The invention extends to any novel one, or any novel combination, of the features disclosed in this specification, as well as to any novel one, or any novel combination, of the steps of the method or process disclosed.
Claims (2)
1. A method for calibrating a triaxial acceleration sensor, comprising:
s1: acquiring a triaxial acceleration data packet of a sensor, wherein the triaxial acceleration data packet comprises a data packet in a static state and data packets in two motion states of the sensor to be corrected;
the triaxial acceleration in the static state is recorded as follows:
；
The triaxial acceleration under two motion states is respectively:
；
；
S2: constructing a relation between the original triaxial data and the 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, values 1-3 respectively represent x, y and z triaxial, The cosine value of the included angle between any two axial directions of the standard triaxial and the original triaxial is expressed;
Recording device Representing raw triaxial data,/>Representing corrected triaxial data, constructing a relationship/>, between the original triaxial data and the corrected triaxial dataThe method is characterized by comprising the following steps:
S3: according to the triaxial acceleration data packet in the static state, calculating the current gravity acceleration and the cosine value of an included angle formed by the original triaxial acceleration and the gravity direction;
The current gravitational acceleration grv is calculated as follows:
Wherein the gravity direction is negative direction of the z axis under the standard posture;
The cosine value of the included angle formed by the original triaxial acceleration and the gravity direction is calculated as follows:
S4: setting constraint conditions, constructing relations between original triaxial acceleration and cosine of a standard X, Y axis clamp angle respectively, and solving according to triaxial acceleration data packets in a motion state and cosine values of included angles formed by the original triaxial acceleration and a gravity direction;
The relation between the original triaxial acceleration and the cosine of the standard X, Y axis clamp angle is specifically expressed as follows:
s5: removing solutions which fail to meet a Cartesian coordinate system through the Euler angle rotation matrix;
Based on the rotation matrix R, the euler angle rotation matrix is known:
cosine value of included angle between original triaxial acceleration and gravity direction Substituting Euler angle rotation matrix and solving/>And/>There are two solutions for each possible value of (a):
For a pair of And/>Combining and substituting the possible solutions respectivelyAnd/>Calculating corresponding through Euler angle rotation matrixAnd/>：
And then willAnd/>Substituting Euler angle rotation matrix and solving/>And comparing with the corresponding solution of the rotation matrix R to obtain the same solution/>Through verification, four solutions in the eight solutions satisfy Cartesian relationship through verification;
Then, any solution is obtained from solutions meeting a Cartesian coordinate system and used as a final correction coefficient, or verification is carried out according to the speed change direction of the advancing direction of the vehicle, and the solution with correct verification is output and used as the final correction coefficient;
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 conditions of the vehicle, marking the triaxial acceleration data packets as-1 for acceleration and-1 for deceleration, and obtaining an actual acceleration and deceleration sequence containing a marking value and an acceleration and deceleration sequence corresponding to each solution;
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 advancing axis x, judging the acceleration and deceleration conditions based on the acceleration, and obtaining acceleration and deceleration sequences corresponding to each solution, wherein the same acceleration is marked as 1 and the deceleration is marked as-1;
And 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 maximum absolute value of the correlation coefficient and positive value as a final solution.
2. The method for correcting a three-axis acceleration sensor according to claim 1, characterized in, that in step S4, the constraint condition includes:
in the completely stationary state, the acceleration in the vehicle forward direction is zero;
in the completely stationary state, the acceleration in the left direction of the vehicle is zero;
Under the motion state, satisfy: acceleration vector sum of horizontal plane = vector difference of vehicle overall acceleration and gravity;
the original triaxial accelerations are mutually perpendicular;
The corrected standard triaxial accelerations are mutually perpendicular.
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| CN116609548B (en) * | 2023-07-20 | 2023-11-03 | 山东省科学院激光研究所 | A three-dimensional fiber optic acceleration sensor system capable of measuring tilt angle |
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Citations (22)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0668485A1 (en) * | 1994-02-18 | 1995-08-23 | VDO Adolf Schindling AG | Method for reproducing vehicle yaw angle from erroneous data |
| US5531115A (en) * | 1995-06-29 | 1996-07-02 | Erdley; Harold F. | Self-calibrating three axis angular rate sensor |
| DE19920968A1 (en) * | 1999-05-06 | 2000-12-14 | Edmund R Poetsch | Arrangement for measurement of movement characterizing values of a moving measurement body including acceleration and inclination has a pendulum for referencing the gravitational vector |
| RU2004107173A (en) * | 2004-03-10 | 2005-10-20 | ЗАО "Газприборавтоматикасервис" (RU) | METHOD OF CALIBRATING THE PARAMETERS OF A PLATFORM INERTIAL MEASURING MODULE |
| CN102298076A (en) * | 2010-04-27 | 2011-12-28 | 美新半导体（无锡）有限公司 | Method and apparatus for calibrating three-axis accelerometer |
| CN103632062A (en) * | 2013-12-06 | 2014-03-12 | 北京乾图方园软件技术有限公司 | Method and device for determining uphill and downhill running states of vehicle by utilizing acceleration sensor and gyroscope |
| CN103675352A (en) * | 2013-12-19 | 2014-03-26 | 中北大学 | Method for comprehensive calibration of static and dynamic parameters of missile strapdown triaxial accelerometer assembly |
| CN103823084A (en) * | 2014-03-21 | 2014-05-28 | 苏州纳芯微电子有限公司 | Method for calibrating three-axis acceleration sensor |
| CN104802697A (en) * | 2015-03-30 | 2015-07-29 | 西北工业大学 | Micro inertial measurement unit and measurement unit based adaptive headlamp control method |
| CN104884902A (en) * | 2012-08-02 | 2015-09-02 | 美新公司 | Method and apparatus for data fusion of a three axis magnetometer and three axis accelerometer |
| CN105807095A (en) * | 2016-03-10 | 2016-07-27 | 同济大学 | Three-axis acceleration sensor mounting error correcting method |
| CN106645799A (en) * | 2016-09-14 | 2017-05-10 | 邹红斌 | Parameter calibration method and apparatus |
| CN107215307A (en) * | 2017-05-24 | 2017-09-29 | 清华大学深圳研究生院 | Driver identity recognition methods and system based on vehicle sensors correction data |
| DE102016221827A1 (en) * | 2016-11-08 | 2018-05-09 | Robert Bosch Gmbh | A method for calibrating a first coordinate system of a three-axis acceleration sensor, which is fixedly arranged in a vehicle, to a second coordinate system of the vehicle and apparatus for calibration |
| CN108398576A (en) * | 2018-03-06 | 2018-08-14 | 中国人民解放军火箭军工程大学 | A kind of static error calibration system and method |
| CN108520571A (en) * | 2018-04-10 | 2018-09-11 | 陈重奋 | Algorithm and device for judging vehicle driving state by using accelerometer |
| CN109085381A (en) * | 2018-09-14 | 2018-12-25 | 上海移为通信技术股份有限公司 | Vehicle-mounted acceleration transducer direction calibration method |
| CN110398244A (en) * | 2019-07-05 | 2019-11-01 | 云南省交通规划设计研究院有限公司 | A kind of inclination of vehicle condition detection method based on acceleration transducer |
| CN110766982A (en) * | 2019-09-26 | 2020-02-07 | 浙江从泰网络科技有限公司 | Vehicle collision detection system based on vehicle-mounted sensor |
| CN111289012A (en) * | 2020-02-20 | 2020-06-16 | 北京邮电大学 | Attitude calibration method and device for sensor |
| CN112444644A (en) * | 2019-08-27 | 2021-03-05 | 株洲中车时代电气股份有限公司 | Calibration method of triaxial accelerometer |
| CN113156167A (en) * | 2021-04-08 | 2021-07-23 | 北京航天发射技术研究所 | Calibration method and device of triaxial accelerometer |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140184509A1 (en) * | 2013-01-02 | 2014-07-03 | Movea Sa | Hand held pointing device with roll compensation |
-
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- 2021-12-31 CN CN202111671265.0A patent/CN114280332B/en active Active
Patent Citations (22)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0668485A1 (en) * | 1994-02-18 | 1995-08-23 | VDO Adolf Schindling AG | Method for reproducing vehicle yaw angle from erroneous data |
| US5531115A (en) * | 1995-06-29 | 1996-07-02 | Erdley; Harold F. | Self-calibrating three axis angular rate sensor |
| DE19920968A1 (en) * | 1999-05-06 | 2000-12-14 | Edmund R Poetsch | Arrangement for measurement of movement characterizing values of a moving measurement body including acceleration and inclination has a pendulum for referencing the gravitational vector |
| RU2004107173A (en) * | 2004-03-10 | 2005-10-20 | ЗАО "Газприборавтоматикасервис" (RU) | METHOD OF CALIBRATING THE PARAMETERS OF A PLATFORM INERTIAL MEASURING MODULE |
| CN102298076A (en) * | 2010-04-27 | 2011-12-28 | 美新半导体（无锡）有限公司 | Method and apparatus for calibrating three-axis accelerometer |
| CN104884902A (en) * | 2012-08-02 | 2015-09-02 | 美新公司 | Method and apparatus for data fusion of a three axis magnetometer and three axis accelerometer |
| CN103632062A (en) * | 2013-12-06 | 2014-03-12 | 北京乾图方园软件技术有限公司 | Method and device for determining uphill and downhill running states of vehicle by utilizing acceleration sensor and gyroscope |
| CN103675352A (en) * | 2013-12-19 | 2014-03-26 | 中北大学 | Method for comprehensive calibration of static and dynamic parameters of missile strapdown triaxial accelerometer assembly |
| CN103823084A (en) * | 2014-03-21 | 2014-05-28 | 苏州纳芯微电子有限公司 | Method for calibrating three-axis acceleration sensor |
| CN104802697A (en) * | 2015-03-30 | 2015-07-29 | 西北工业大学 | Micro inertial measurement unit and measurement unit based adaptive headlamp control method |
| CN105807095A (en) * | 2016-03-10 | 2016-07-27 | 同济大学 | Three-axis acceleration sensor mounting error correcting method |
| CN106645799A (en) * | 2016-09-14 | 2017-05-10 | 邹红斌 | Parameter calibration method and apparatus |
| DE102016221827A1 (en) * | 2016-11-08 | 2018-05-09 | Robert Bosch Gmbh | A method for calibrating a first coordinate system of a three-axis acceleration sensor, which is fixedly arranged in a vehicle, to a second coordinate system of the vehicle and apparatus for calibration |
| CN107215307A (en) * | 2017-05-24 | 2017-09-29 | 清华大学深圳研究生院 | Driver identity recognition methods and system based on vehicle sensors correction data |
| CN108398576A (en) * | 2018-03-06 | 2018-08-14 | 中国人民解放军火箭军工程大学 | A kind of static error calibration system and method |
| CN108520571A (en) * | 2018-04-10 | 2018-09-11 | 陈重奋 | Algorithm and device for judging vehicle driving state by using accelerometer |
| CN109085381A (en) * | 2018-09-14 | 2018-12-25 | 上海移为通信技术股份有限公司 | Vehicle-mounted acceleration transducer direction calibration method |
| CN110398244A (en) * | 2019-07-05 | 2019-11-01 | 云南省交通规划设计研究院有限公司 | A kind of inclination of vehicle condition detection method based on acceleration transducer |
| CN112444644A (en) * | 2019-08-27 | 2021-03-05 | 株洲中车时代电气股份有限公司 | Calibration method of triaxial accelerometer |
| CN110766982A (en) * | 2019-09-26 | 2020-02-07 | 浙江从泰网络科技有限公司 | Vehicle collision detection system based on vehicle-mounted sensor |
| CN111289012A (en) * | 2020-02-20 | 2020-06-16 | 北京邮电大学 | Attitude calibration method and device for sensor |
| CN113156167A (en) * | 2021-04-08 | 2021-07-23 | 北京航天发射技术研究所 | Calibration method and device of triaxial accelerometer |
Non-Patent Citations (5)
| Title |
|---|
| Calibration of MEMS Sensors for Precision Measurement of Acceleration, Spin and Attitude;A. W. Lodhi;2021 IEEE 32nd International Conference on Microelectronics (MIEL);20210914;全文 * |
| Calibration of three-axis MEMS angular rate sensor based;Kachanov, B.O;Sensors and Systems;20181231;全文 * |
| 三轴加速度传感器校正方法研究;林生荣;传感器与微系统;20111120;全文 * |
| 基于三轴加速度计的多维力传感器静态自校正;王嘉力;仪器仪表学报;20080215;全文 * |
| 陆欣 ; .三轴MEMS加速度计的最大似然校正算法.国防科技大学学报.2017,全文. * |
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