CN108496059B - Method and device for correcting inertia sensor, terminal equipment and storage medium - Google Patents
Method and device for correcting inertia sensor, terminal equipment and storage medium Download PDFInfo
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- CN108496059B CN108496059B CN201880000222.XA CN201880000222A CN108496059B CN 108496059 B CN108496059 B CN 108496059B CN 201880000222 A CN201880000222 A CN 201880000222A CN 108496059 B CN108496059 B CN 108496059B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
- G01C25/005—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass initial alignment, calibration or starting-up of inertial devices
Abstract
The invention relates to the technical field of sensors, and provides a method and a device for correcting an inertia sensor, terminal equipment and a computer storage medium. The method comprises the following steps: correcting data output by an inertia sensor according to a target deviation, wherein an initial value of the target deviation is a deviation value obtained by first correction after the inertia sensor is installed; when the inertia sensor is switched from a motion state to a static state, acquiring target data output by the inertia sensor; calculating a deviation value between the target data and a preset theoretical inertia value; and updating the target deviation by using the calculated deviation value. If the inertia sensor is installed on a running vehicle, the deviation for data correction can be updated once in real time when the vehicle stops every time, so that the problem of inaccurate deviation caused by variation of actual deviation after single static correction can be effectively solved, and the data accuracy of the inertia sensor system is improved.
Description
Technical Field
The present invention relates to the field of sensor technologies, and in particular, to a method and an apparatus for calibrating an inertia sensor, a terminal device, and a computer storage medium.
Background
The inertia sensor is widely applied to the field of vehicle-mounted security, and the accuracy of data of the inertia sensor plays an important role in analyzing the posture of a vehicle. The inertia sensor can be manually and statically corrected after being installed for the first time, and data correction is carried out subsequently according to the deviation obtained by the first correction. However, as the vehicle jolts, the installation angle and the installation position of the inertia sensor may change, which may cause a change in actual data deviation, and at this time, if the deviation obtained by the first correction is still used for data correction, the deviation between the corrected data and the true value is large, so that the data accuracy of the entire inertia sensor system is reduced.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for calibrating an inertia sensor, a terminal device, and a computer storage medium, which can improve data accuracy of an inertia sensor system.
A first aspect of an embodiment of the present invention provides a method for correcting an inertia sensor, including:
correcting data output by an inertia sensor according to a target deviation, wherein an initial value of the target deviation is a deviation value obtained by first correction after the inertia sensor is installed;
when the inertia sensor is switched from a motion state to a static state, acquiring target data output by the inertia sensor;
calculating a deviation value between the target data and a preset theoretical inertia value, wherein the theoretical inertia value is an inertia value which should be theoretically output when the inertia sensor is static;
and updating the target deviation by adopting the calculated deviation value.
A second aspect of an embodiment of the present invention provides a calibration apparatus for an inertia sensor, including:
the data correction module is used for correcting data output by the inertia sensor according to target deviation, and the initial value of the target deviation is a deviation value obtained by first correction after the inertia sensor is installed;
the target data acquisition module is used for acquiring target data output by the inertia sensor when the inertia sensor is switched from a motion state to a static state;
the deviation value calculating module is used for calculating a deviation value between the target data and a preset theoretical inertia value, wherein the theoretical inertia value is an inertia value which should be theoretically output when the inertia sensor is static;
and the deviation updating module is used for updating the target deviation by adopting the calculated deviation value.
A third aspect of the embodiments of the present invention provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the method for correcting an inertia sensor according to the first aspect of the embodiments of the present invention when executing the computer program.
A fourth aspect of embodiments of the present invention provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the steps of the method for correcting an inertia sensor as provided in the first aspect of embodiments of the present invention.
In the embodiment of the invention, data output by an inertia sensor is corrected according to target deviation, and the initial value of the target deviation is a deviation value obtained by first correction after the inertia sensor is installed; when the inertia sensor is switched from a motion state to a static state, acquiring target data output by the inertia sensor; calculating a deviation value between the target data and a preset theoretical inertia value, wherein the theoretical inertia value is an inertia value which should be theoretically output when the inertia sensor is static; and updating the target deviation by using the calculated deviation value. If the inertia sensor is installed on a running vehicle, the inertia sensor can be detected to be switched from a moving state to a static state during each parking of the vehicle, target data output by the inertia sensor is collected at the moment, then a deviation value between the target data and a theoretical inertia value is calculated, and a target deviation for data correction is updated by the calculated deviation value. Obviously, the deviation used for data correction is updated once in real time when the vehicle parks every time, so that the problem of inaccurate deviation caused by variation of actual deviation after the traditional single static correction can be effectively solved, the deviation of corrected data and a true value is ensured to be small, and the data accuracy of the inertia sensor system is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a flowchart of a first embodiment of a calibration method for an inertia sensor according to an embodiment of the present invention;
fig. 2 is a flowchart of a second embodiment of a calibration method for an inertia sensor according to an embodiment of the present invention;
FIG. 3 is a block diagram of one embodiment of a calibration apparatus for an inertial sensor, according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a terminal device according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
The embodiment of the invention provides a method and a device for correcting an inertia sensor, terminal equipment and a computer storage medium, which can improve the data accuracy of an inertia sensor system.
Referring to fig. 1, a first embodiment of a calibration method for an inertia sensor according to an embodiment of the present invention includes:
101. correcting data output by the inertia sensor according to the target deviation;
in the embodiment of the present invention, the inertia sensor may be mounted on any moving object (e.g., a vehicle, a ship) for detecting inertia data of the moving object. Data collected and output by the inertia sensor is corrected according to a target deviation, wherein the target deviation is a variable, an initial value of the target deviation is a deviation value obtained by first correction after the inertia sensor is installed, and the target deviation is updated through the following steps 102 to 104. After the inertia sensor is installed, the target deviation is adopted to correct the data output by the inertia sensor until the whole data acquisition process is finished. Specifically, taking a three-axis inertia sensor as an example, if data output by the sensor is x, y, z, and target deviations are Δ x, Δ y, Δ z, the corrected data are x- Δ x, y- Δ y, z- Δ z.
102. When the inertia sensor is switched from a motion state to a static state, acquiring target data output by the inertia sensor;
and when the inertia sensor is switched from a motion state to a static state, acquiring target data output by the inertia sensor. The dynamic and static states of the inertia sensor are equivalent to the dynamic and static states of the object mounted on the inertia sensor, so that the inertia sensor is switched from the moving state to the static state, and the object mounted on the inertia sensor is switched from the moving state to the static state, for example, after the running vehicle is stopped. And when the inertia sensor is in a static state, acquiring target data output by the inertia sensor, wherein the target data is original inertia data acquired at the current moment, namely uncorrected data.
Specifically, the inertia sensor is mounted on the vehicle, and whether the inertia sensor is in a stationary state may be determined in the following 3 ways.
Mode 1: acquiring satellite navigation positioning information of the vehicle; determining the speed of the vehicle according to the satellite navigation positioning information; and if the speed of the vehicle is kept to be 0 in the second time period, determining that the inertia sensor is in a static state.
For example, real-time GPS positioning information of the vehicle is acquired, the speed of the vehicle may be determined according to the positioning information, and if it is determined that the speed of the vehicle is maintained at 0 for a second time period (e.g., 5 seconds), it may be determined that the inertia sensor is in a stationary state.
Mode 2: obtaining a speed of the vehicle from a driveline of the vehicle; and if the speed of the vehicle is 0, determining that the inertia sensor is in a static state.
The real-time speed parameter of the vehicle can be output by the transmission system of the vehicle, so that the speed of the vehicle can be directly obtained from the transmission system of the vehicle; and if the acquired vehicle speed is 0, determining that the inertia sensor is in a static state.
Mode 3: and if the fluctuation range of the data output by the inertia sensor in the third time length is smaller than a preset threshold value, judging that the inertia sensor is in a static state.
When the vehicle moves (does not keep moving at a constant speed), the inertia value of the vehicle changes greatly, namely the fluctuation range of the data output by the inertia sensor is large. When the vehicle is stationary or continuously in constant-speed motion, the inertia value is theoretically unchanged, and the actual change amplitude is small, so if it is detected that the fluctuation range of the data output by the inertia sensor in a third time period (for example, 5 seconds) is smaller than a preset threshold value, it can be determined that the inertia sensor is in a stationary state (based on that the vehicle is hardly in an absolute constant-speed motion state in an actual situation).
Further, in order to improve the accuracy of determining whether the inertia sensor is in a static state, the above 3 manners may also be used in combination, for example, the manner 2+ manner 3 is adopted for determination, or the manner 1+ manner 3 is adopted for determination.
103. Calculating a deviation value between the target data and a preset theoretical inertia value;
after the target data are collected, calculating a deviation value between the target data and a preset theoretical inertia value. The theoretical inertia value here is an inertia value that the inertia sensor should theoretically output when the inertia sensor is stationary, for example, for a stationary three-axis inertia sensor, the theoretical inertia value is X-0, Y-0, and Z-1. Assuming that the target data is X, Y and Z and the corresponding theoretical inertia values are X, Y and Z, the calculated deviation values are X-X, Y-Y and Z-Z.
104. And updating the target deviation by adopting the calculated deviation value.
And after calculating to obtain a deviation value between the target data and a preset theoretical inertia value, updating the target deviation by using the deviation value, namely replacing the original deviation value of the target deviation with the calculated deviation value at the current moment. And after the target deviation is updated, correcting the data output by the inertia sensor according to the updated target deviation. Obviously, each time the inertia sensor switches from a moving state to a stationary state, a new deviation value is calculated, and the target deviation is updated with the calculated deviation value. If the inertia sensor is mounted on a running vehicle, the target deviation is updated once every time the vehicle stops, which is equivalent to adjusting the target deviation for multiple times in the running process of the vehicle, so that the target deviation and the accuracy of corrected data are improved.
In the embodiment of the invention, data output by an inertia sensor is corrected according to target deviation, and the initial value of the target deviation is a deviation value obtained by first correction after the inertia sensor is installed; when the inertia sensor is switched from a motion state to a static state, acquiring target data output by the inertia sensor; calculating a deviation value between the target data and a preset theoretical inertia value, wherein the theoretical inertia value is an inertia value which should be theoretically output when the inertia sensor is static; and updating the target deviation by using the calculated deviation value. If the inertia sensor is installed on a running vehicle, the inertia sensor can be detected to be switched from a moving state to a static state during each parking of the vehicle, target data output by the inertia sensor is collected at the moment, then a deviation value between the target data and a theoretical inertia value is calculated, and a target deviation for data correction is updated by the calculated deviation value. Obviously, the deviation used for data correction is updated once in real time when the vehicle parks every time, so that the problem of inaccurate deviation caused by variation of actual deviation after the traditional single static correction can be effectively solved, the deviation of corrected data and a true value is ensured to be small, and the data accuracy of the inertia sensor system is improved.
Referring to fig. 2, a second embodiment of a calibration method for an inertia sensor according to an embodiment of the present invention includes:
201. correcting data output by the inertia sensor according to the target deviation;
step 201 is the same as step 101, and specific reference may be made to the related description of step 101.
202. When the inertia sensor is switched from a motion state to a static state, acquiring data output by the inertia sensor for multiple times within a first time length to obtain multiple groups of inertia data;
step 202 collects data multiple times as compared to collecting data once in step 102. When the inertia sensor is detected to be switched from a motion state to a static state, data output by the inertia sensor are collected for multiple times within a first time length, and multiple groups of inertia data are obtained. For example, 100 times of data output by the inertia sensor is collected within 1 second to obtain 100 sets of inertia data, and each set of inertia data can be expressed as { x, y, z } for the three-axis inertia sensor.
203. Determining the average value or the maximum value of the multiple groups of inertia data as target data;
after obtaining the plurality of sets of inertia data, determining the average value or the maximum value of the plurality of sets of inertia data as target data. The definition and the action of the target data are the same as those of the target data in the step 102, and the original inertia data closer to the real value can be obtained by solving the average value or the maximum value, which is beneficial to the subsequent calculation of more accurate deviation value for updating the target deviation.
204. Obtaining a first deviation value by subtracting the target data from the theoretical inertia value;
after obtaining the target data, the target data is subtracted from the theoretical inertia value, which is defined as the theoretical inertia value in step 103, to obtain a first deviation value.
205. Acquiring a historical deviation value of the target deviation;
and acquiring a historical deviation value of the target deviation, wherein the historical deviation value comprises an initial value of the target deviation and a deviation value after each updating. For example, if the target offset is updated once before the current time, the historical offset value includes 2 offset values in total, which are the initial value (the offset value obtained by first correcting the installed inertia sensor) and the offset value obtained by updating the initial value; if the target offset is updated 10 times before the current time, the historical offset values include 11 offset values for the initial value and the 10 updated offset values. And recording and storing the updated deviation value when the target deviation is updated every time, and forming the historical deviation value.
Further, step 205 may specifically include:
(1) judging whether the number of the historical deviation values is smaller than or equal to a preset first number, if so, executing the step (2), and otherwise, executing the step (3);
(2) acquiring all historical deviation values of the target deviation;
(3) and acquiring a first number of historical deviation values of which the corresponding updating time is closest to the current time in the historical deviation values of the target deviation.
For the above steps (1) to (3), first, it is determined whether the number of the recorded historical deviation values is less than or equal to a preset first number (for example, 20), and if so, all the historical deviation values of the target deviation are obtained; and if the number of the historical deviation values is larger than the first number, acquiring a first number of historical deviation values of which the corresponding updating time is closest to the current time in the historical deviation values of the target deviation. Assuming that the first number is 20, if the target deviation is updated 10 times, that is, the number of the historical deviation values is 11, all the 11 historical deviation values are acquired; if the target deviation is updated 30 times, that is, the number of the historical deviation values is 31, 20 historical deviation values of the 31 historical deviation values, which have the updating time closest to the current time, are obtained, that is, the deviation values obtained by updating 11 th to 30 th times. By such an arrangement, when the number of history offset values is excessive, the history offset value with an earlier update time can be ignored, thereby reducing the amount of calculation in the subsequent step. In addition, the historical deviation value with the earlier updating time can be deleted, so that the occupied storage space is reduced.
206. Determining the first deviation value and the average value of the obtained historical deviation values as the deviation value between the target data and the theoretical inertia value;
after obtaining the historical deviation value of the target deviation, determining the average value of the first deviation value and the obtained historical deviation value as the deviation value between the target data and the theoretical inertia value. In steps 205 and 206, a deviation counting process is performed, and the actual deviation condition of the inertia sensor can be reflected more truly by counting the deviation values used in multiple updates and calculating an average value, so as to obtain a more accurate deviation value for updating the target deviation.
Optionally, in step 206, an average value after removing the maximum and minimum values may be adopted, or other data processing manners in data statistics and analysis may be adopted.
207. And updating the target deviation by adopting a deviation value between the target data and the theoretical inertia value.
And after a deviation value between the target data and the theoretical inertia value is obtained, updating the target deviation by using the deviation value. And after the target deviation is updated, correcting the data output by the inertia sensor according to the updated target deviation.
In the embodiment of the invention, the data output by the inertia sensor is corrected according to the target deviation; when the inertia sensor is switched from a motion state to a static state, acquiring data output by the inertia sensor for multiple times within a first time length to obtain multiple groups of inertia data; determining the average value or the maximum value of the multiple groups of inertia data as target data; obtaining a first deviation value by subtracting the target data from the theoretical inertia value; acquiring a historical deviation value of the target deviation; determining the first deviation value and the average value of the obtained historical deviation values as the deviation value between the target data and the theoretical inertia value; and updating the target deviation by adopting a deviation value between the target data and the theoretical inertia value. Compared with the first embodiment of the invention, the embodiment determines the target data by acquiring a plurality of groups of inertia data and calculating the average value or the maximum value, and can acquire the original inertia data which is closer to the real value; and through the deviation statistics mode, more accurate deviation values for updating the target deviation can be obtained, namely, more accurate target deviation is obtained, so that the data accuracy of the inertia sensor system is further improved.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
The above mainly describes a method for calibrating an inertia sensor, and a calibration apparatus for an inertia sensor will be described below.
Referring to fig. 3, an embodiment of a calibration apparatus for an inertia sensor according to an embodiment of the present invention includes:
the data correction module 301 is configured to correct data output by an inertia sensor according to a target deviation, where an initial value of the target deviation is a deviation value obtained by first correcting the inertia sensor after the inertia sensor is installed;
a target data collecting module 302, configured to collect target data output by the inertia sensor when the inertia sensor is switched from a moving state to a stationary state;
a deviation value calculating module 303, configured to calculate a deviation value between the target data and a preset theoretical inertia value, where the theoretical inertia value is an inertia value that the inertia sensor should theoretically output when the inertia sensor is stationary;
and a deviation updating module 304, configured to update the target deviation by using the calculated deviation value.
Further, the target data acquisition module 302 may include:
the data acquisition unit is used for acquiring data output by the inertia sensor for multiple times within a first time length to obtain multiple groups of inertia data;
and the data determining unit is used for determining the average value or the maximum value of the plurality of groups of inertia data as the target data.
Further, the deviation value calculating module 303 may include:
the difference making unit is used for making a difference between the target data and the theoretical inertia value to obtain a first deviation value;
a historical deviation value obtaining unit, configured to obtain a historical deviation value of the target deviation, where the historical deviation value includes an initial value of the target deviation and a deviation value after each update;
and the deviation value determining unit is used for determining the average value of the first deviation value and the acquired historical deviation value as the deviation value between the original data and the theoretical inertia value.
An embodiment of the present invention further provides a terminal device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the method for calibrating an inertia sensor as shown in fig. 1 or fig. 2 when executing the computer program.
Embodiments of the present invention further provide a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program implements the steps of the calibration method for an inertia sensor as shown in fig. 1 or fig. 2.
Fig. 4 is a schematic diagram of a terminal device according to an embodiment of the present invention. As shown in fig. 4, the terminal device 4 of this embodiment includes: a processor 40, a memory 41 and a computer program 42 stored in said memory 41 and executable on said processor 40. The processor 40, when executing the computer program 42, implements the steps in the embodiments of the calibration method for each inertia sensor described above, such as the steps 101 to 104 shown in fig. 1. Alternatively, the processor 40, when executing the computer program 42, implements the functions of the modules/units in the above-mentioned device embodiments, such as the functions of the modules 301 to 304 shown in fig. 3.
The computer program 42 may be partitioned into one or more modules/units that are stored in the memory 41 and executed by the processor 40 to implement the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program 42 in the terminal device 4.
The terminal device 4 may be various types of computing devices such as a mobile phone, a desktop computer, a notebook, a palm computer, and a cloud server. The terminal device may include, but is not limited to, a processor 40, a memory 41. It will be understood by those skilled in the art that fig. 4 is only an example of the terminal device 4, and does not constitute a limitation to the terminal device 4, and may include more or less components than those shown, or combine some components, or different components, for example, the terminal device 4 may further include an input-output device, a network access device, a bus, etc.
The Processor 40 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 41 may be an internal storage unit of the terminal device 4, such as a hard disk or a memory of the terminal device 4. The memory 41 may also be an external storage device of the terminal device 4, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the terminal device 4. Further, the memory 41 may also include both an internal storage unit and an external storage device of the terminal device 4. The memory 41 is used for storing the computer program and other programs and data required by the terminal device. The memory 41 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described system embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, etc. It should be noted that the computer readable medium may contain other components which may be suitably increased or decreased as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media which may not include electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (7)
1. A method of calibrating an inertial sensor, comprising:
correcting data output by an inertia sensor according to a target deviation, wherein an initial value of the target deviation is a deviation value obtained by first correction after the inertia sensor is installed;
when the inertia sensor is switched from a motion state to a static state, acquiring target data output by the inertia sensor;
calculating a deviation value between the target data and a preset theoretical inertia value, wherein the theoretical inertia value is an inertia value which should be theoretically output when the inertia sensor is static;
updating the target deviation by adopting the calculated deviation value;
wherein the calculating of the deviation value between the target data and a preset theoretical inertia value comprises:
obtaining a first deviation value by subtracting the target data from the theoretical inertia value;
acquiring a historical deviation value of the target deviation, wherein the historical deviation value comprises an initial value of the target deviation and a deviation value after each updating;
determining the first deviation value and the average value of the obtained historical deviation values as the deviation value between the target data and a preset theoretical inertia value;
the acquiring the historical deviation value of the target deviation comprises:
if the number of the historical deviation values is smaller than or equal to a preset first number, acquiring all historical deviation values of the target deviation;
and if the number of the historical deviation values is larger than the first number, acquiring a first number of historical deviation values of which the corresponding updating time is closest to the current time in the historical deviation values of the target deviation.
2. The method of calibrating an inertial sensor of claim 1, wherein the acquiring target data output by the inertial sensor comprises:
acquiring data output by the inertia sensor for multiple times within a first time length to obtain multiple groups of inertia data;
determining the average value or the maximum value of the plurality of groups of inertia data as the target data.
3. The method of calibrating an inertia sensor according to claim 1 or 2, wherein the inertia sensor is mounted on a vehicle, and whether the inertia sensor is in a stationary state is determined by:
acquiring satellite navigation positioning information of the vehicle;
determining the speed of the vehicle according to the satellite navigation positioning information;
if the speed of the vehicle is kept to be 0 in a second time period, determining that the inertia sensor is in a static state;
or
Obtaining a speed of the vehicle from a driveline of the vehicle;
if the speed of the vehicle is 0, determining that the inertia sensor is in a static state;
or
And if the fluctuation range of the data output by the inertia sensor in the third time length is smaller than a preset threshold value, judging that the inertia sensor is in a static state.
4. An inertia sensor calibration apparatus, comprising:
the data correction module is used for correcting data output by the inertia sensor according to target deviation, and the initial value of the target deviation is a deviation value obtained by first correction after the inertia sensor is installed;
the target data acquisition module is used for acquiring target data output by the inertia sensor when the inertia sensor is switched from a motion state to a static state;
the deviation value calculating module is used for calculating a deviation value between the target data and a preset theoretical inertia value, wherein the theoretical inertia value is an inertia value which should be theoretically output when the inertia sensor is static;
the deviation updating module is used for updating the target deviation by adopting the calculated deviation value;
wherein, the deviation value calculation module comprises:
the difference making unit is used for making a difference between the target data and the theoretical inertia value to obtain a first deviation value;
a historical deviation value obtaining unit, configured to obtain a historical deviation value of the target deviation, where the historical deviation value includes an initial value of the target deviation and a deviation value after each update;
the deviation value determining unit is used for determining the average value of the first deviation value and the obtained historical deviation value as a deviation value between the target data and a theoretical inertia value;
the acquiring the historical deviation value of the target deviation comprises:
if the number of the historical deviation values is smaller than or equal to a preset first number, acquiring all historical deviation values of the target deviation;
and if the number of the historical deviation values is larger than the first number, acquiring a first number of historical deviation values of which the corresponding updating time is closest to the current time in the historical deviation values of the target deviation.
5. The inertial sensor calibration device of claim 4, wherein the target data acquisition module comprises:
the data acquisition unit is used for acquiring data output by the inertia sensor for multiple times within a first time length to obtain multiple groups of inertia data;
and the data determining unit is used for determining the average value or the maximum value of the plurality of groups of inertia data as the target data.
6. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method for correction of an inertia sensor according to any one of claims 1 to 3 when executing the computer program.
7. A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of correction of an inertia sensor according to any one of claims 1 to 3.
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| PCT/CN2018/080472 WO2019183750A1 (en) | 2018-03-26 | 2018-03-26 | Inertia sensor correction method and apparatus, terminal device and storage medium |
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| CN110514227A (en) * | 2019-09-04 | 2019-11-29 | 惠州Tcl移动通信有限公司 | Acquisition methods, mobile terminal and the storage medium of bearing data calibration parameter |
| CN112557996B (en) * | 2019-09-26 | 2023-11-03 | 深圳电蚂蚁数据技术有限公司 | Electric energy measurement system convenient for error verification and error verification method |
| CN114152806B (en) * | 2020-09-08 | 2024-03-15 | 武汉国测数据技术有限公司 | Electric energy sensor with three-way array structure and measurement system and method formed by same |
| CN114152810B (en) * | 2020-09-08 | 2024-03-15 | 武汉国测数据技术有限公司 | Three-phase electric energy sensor with three-way array structure and measuring system and method thereof |
| CN114152791B (en) * | 2020-09-08 | 2024-03-15 | 武汉国测数据技术有限公司 | Three-meter-method three-phase electric energy meter structure with user self-checking error and checking method |
| CN114152809B (en) * | 2020-09-08 | 2024-03-15 | 武汉国测数据技术有限公司 | Smart electric meter with error self-checking function and checking method thereof |
| CN114152811B (en) * | 2020-09-08 | 2024-03-15 | 武汉国测数据技术有限公司 | Electric energy meter with three-way array structure and measuring system and measuring method formed by electric energy meter |
| CN112902988A (en) * | 2021-03-12 | 2021-06-04 | Oppo广东移动通信有限公司 | Parameter calibration method, device, terminal and storage medium |
| CN116879578A (en) * | 2023-06-21 | 2023-10-13 | 清华大学 | Road acceleration sensor, control method and control device thereof |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5065612A (en) * | 1988-09-28 | 1991-11-19 | Sumitomo Electric Industries, Ltd. | Method of correcting zero point of gyro and apparatus therefor |
| CN101233390A (en) * | 2005-08-01 | 2008-07-30 | 丰田自动车株式会社 | Zero point correction device of angular velocity sensor |
| CN103782180A (en) * | 2011-09-08 | 2014-05-07 | 莱卡地球系统公开股份有限公司 | Method and system of recalibrating an inertial sensor |
| CN103782179A (en) * | 2011-09-08 | 2014-05-07 | 莱卡地球系统公开股份有限公司 | Method of recalibrating inertial sensors |
| CN105074649A (en) * | 2013-03-15 | 2015-11-18 | 奥托里夫Asp股份有限公司 | System and method for inertial sensor offset compensation |
| WO2016208440A1 (en) * | 2015-06-26 | 2016-12-29 | 株式会社デンソー | Output correction device for sensor |
| CN107515011A (en) * | 2017-07-07 | 2017-12-26 | 青岛海信移动通信技术股份有限公司 | A kind of bearing calibration of gyroscope and device |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9074888B2 (en) * | 2013-01-28 | 2015-07-07 | Drs Sustainment Systems, Inc. | Gyro drift cancelation |
| CN103731555B (en) * | 2014-01-01 | 2016-03-09 | 厦门美图之家科技有限公司 | A kind of alarm clock prompting method of mobile terminal and device |
-
2018
- 2018-03-26 CN CN201880000222.XA patent/CN108496059B/en active Active
- 2018-03-26 WO PCT/CN2018/080472 patent/WO2019183750A1/en active Application Filing
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5065612A (en) * | 1988-09-28 | 1991-11-19 | Sumitomo Electric Industries, Ltd. | Method of correcting zero point of gyro and apparatus therefor |
| CN101233390A (en) * | 2005-08-01 | 2008-07-30 | 丰田自动车株式会社 | Zero point correction device of angular velocity sensor |
| CN103782180A (en) * | 2011-09-08 | 2014-05-07 | 莱卡地球系统公开股份有限公司 | Method and system of recalibrating an inertial sensor |
| CN103782179A (en) * | 2011-09-08 | 2014-05-07 | 莱卡地球系统公开股份有限公司 | Method of recalibrating inertial sensors |
| CN105074649A (en) * | 2013-03-15 | 2015-11-18 | 奥托里夫Asp股份有限公司 | System and method for inertial sensor offset compensation |
| WO2016208440A1 (en) * | 2015-06-26 | 2016-12-29 | 株式会社デンソー | Output correction device for sensor |
| CN107515011A (en) * | 2017-07-07 | 2017-12-26 | 青岛海信移动通信技术股份有限公司 | A kind of bearing calibration of gyroscope and device |
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| CN108496059A (en) | 2018-09-04 |
| WO2019183750A1 (en) | 2019-10-03 |
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