1. A sensor calibration method is characterized by comprising the following steps:

a calibration processing step, wherein the calibration processing step comprises:

controlling the rotation of the three-axis turntable according to the turntable control information, wherein the turntable control information comprises: controlling the working mode and the rotation rate of a three-axis turntable set by a computer through the turntable;

acquiring rotation data of the three-axis turntable through an inertial sensor, and sending the rotation data to a data acquisition computer;

instructing the data acquisition computer to build a sensor error model of the inertial sensor;

and carrying out data analysis processing on the rotation data through a sensor error model to obtain parameter data, and calibrating the inertial sensor according to the parameter data.

2. The method of claim 1, wherein after calibrating the inertial sensor based on the parameter data, the method further comprises:

under the condition that the difference value between the rotation data and the parameter data is smaller than a preset threshold value, finishing the calibration processing;

and under the condition that the difference value between the rotation data and the parameter data is larger than the preset threshold value, circularly executing the calibration processing step until the difference value between the rotation data and the parameter data is smaller than the preset threshold value.

3. The method of claim 1, wherein data parsing the rotational data through a sensor error model comprises:

in a case where the sensor error model includes a gyroscope error model, determining the following gyroscope equation as the gyroscope error model:

u＝ω₀+K_gω, u is the output of the gyroscope, w₀Is the zero bias of the gyroscope, ω is the input of the gyroscope, K_gA scale factor of the gyroscope;

and inputting the rotation data into the gyroscope formula so as to analyze and process the rotation data.

4. The method of claim 1, wherein data parsing the rotational data through a sensor error model comprises:

in the case where the sensor error model comprises an accelerometer error model, determining as the accelerometer error model the following acceleration formula:

f＝a₀+K_aa, f are the output of the accelerometer, a₀Is the zero offset of the accelerometer, a is the input of the accelerometer, K_aIs a scale factor of the accelerometer;

and inputting the rotation data into the acceleration formula to perform data analysis processing on the rotation data.

5. The method of claim 3, wherein performing data analysis on the rotational data through a sensor error model to obtain parameter data, and performing calibration processing on the inertial sensor according to the parameter data comprises:

inputting the rotation data into the gyroscope error model to obtain gyroscope output data;

and under the condition that the inertial sensor comprises a gyroscope, calibrating the gyroscope according to the output data of the gyroscope.

6. The method of claim 4, wherein performing data analysis processing on the rotation data through a sensor error model to obtain parameter data, and performing calibration processing on the inertial sensor according to the parameter data comprises:

inputting the rotation data into the accelerometer error model to obtain acceleration output data;

and under the condition that the inertial sensor comprises an accelerometer, calibrating the accelerometer according to the acceleration output data.

7. A sensor calibration device, comprising:

the control module is used for controlling the rotation of the three-axis turntable according to the turntable control information, wherein the turntable control information comprises: controlling the working mode and the rotation rate of a three-axis turntable set by a computer through the turntable;

the acquisition module is used for acquiring the rotation data of the three-axis turntable through the inertial sensor and sending the rotation data to the data acquisition computer;

the modeling module is used for indicating the data acquisition computer to establish a sensor error model of the inertial sensor;

and the analysis module is used for carrying out data analysis processing on the rotation data through a sensor error model to obtain parameter data and carrying out calibration processing on the inertial sensor according to the parameter data.

8. The apparatus of claim 7, wherein the parsing module is further configured to:

under the condition that the difference value between the rotation data and the parameter data is smaller than a preset threshold value, finishing the calibration processing;

and under the condition that the difference value between the rotation data and the parameter data is larger than the preset threshold value, circularly executing the calibration processing step until the difference value between the rotation data and the parameter data is smaller than the preset threshold value.

9. A computer-readable storage medium, comprising a stored program, wherein the program is operable to perform the method of any one of claims 1 to 6.

10. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to execute the method of any of claims 1 to 6 by means of the computer program.

Background

With the development of science and technology, various sensors are widely applied to the fields of life, military, navigation, aerospace, detection and the like, and corresponding sensors are needed to be used in every place where data collection is needed. For the subsequent data processing and the accuracy of the data processing result, the accuracy requirement for the data collected by the sensor is very high, and therefore the calibration of the sensor is particularly important. In the prior art, a polynomial error model is used for calibrating the sensor. The multi-position calibration method adopted by the error model in the polynomial form ignores a high-order coupling term hidden in the polynomial, ignores the time-varying characteristic of model parameters in the calibration process, and is difficult to obtain the expected calibration effect.

Aiming at the problem of poor calibration effect on the sensor in the related art, an effective solution is not provided.

Disclosure of Invention

The embodiment of the invention provides a sensor calibration method and device, a storage medium and an electronic device, and aims to solve the problem that the sensor calibration effect is poor in the related art.

According to an embodiment of the present invention, there is provided a sensor calibration method including: a calibration processing step, wherein the calibration processing step comprises: controlling the rotation of the three-axis turntable according to the turntable control information, wherein the turntable control information comprises: controlling the working mode and the rotation rate of a three-axis turntable set by a computer through the turntable; acquiring rotation data of the three-axis turntable through an inertial sensor, and sending the rotation data to a data acquisition computer; instructing the data acquisition computer to build a sensor error model of the inertial sensor; and carrying out data analysis processing on the rotation data through a sensor error model to obtain parameter data, and calibrating the inertial sensor according to the parameter data.

Optionally, after the calibration processing is performed on the inertial sensor according to the parameter data, the method further includes: under the condition that the difference value between the rotation data and the parameter data is smaller than a preset threshold value, finishing the calibration processing; and under the condition that the difference value between the rotation data and the parameter data is larger than the preset threshold value, circularly executing the calibration processing step until the difference value between the rotation data and the parameter data is smaller than the preset threshold value.

Optionally, the data analysis processing of the rotation data by the sensor error model includes: in a case where the sensor error model includes a gyroscope error model, determining the following gyroscope equation as the gyroscope error model: u- ω₀+K_gω, u is the output of the gyroscope, w₀Is the zero bias of the gyroscope, ω is the input of the gyroscope, K_gA scale factor of the gyroscope; and inputting the rotation data into the gyroscope formula so as to analyze and process the rotation data.

Optionally, the data analysis processing of the rotation data by the sensor error model includes: in the case where the sensor error model comprises an accelerometer error model, determining as the accelerometer error model the following acceleration formula: a is₀+K_aa, f are the output of the accelerometer, a₀Is the zero offset of the accelerometer, a is the input of the accelerometer, K_aIs a scale factor of the accelerometer; and inputting the rotation data into the acceleration formula to perform data analysis processing on the rotation data.

Optionally, the data analysis processing is performed on the rotation data through a sensor error model to obtain parameter data, and the calibration processing is performed on the inertial sensor according to the parameter data, including: inputting the rotation data into the gyroscope error model to obtain gyroscope output data; and under the condition that the inertial sensor comprises a gyroscope, calibrating the gyroscope according to the output data of the gyroscope.

Optionally, the data analysis processing is performed on the rotation data through a sensor error model to obtain parameter data, and the calibration processing is performed on the inertial sensor according to the parameter data, including: inputting the rotation data into the accelerometer error model to obtain acceleration output data; and under the condition that the inertial sensor comprises an accelerometer, calibrating the accelerometer according to the acceleration output data.

According to an embodiment of the present invention, there is provided a sensor calibration apparatus including: the control module is used for controlling the rotation of the three-axis turntable according to the turntable control information, wherein the turntable control information comprises: controlling the working mode and the rotation rate of a three-axis turntable set by a computer through the turntable; the acquisition module is used for acquiring the rotation data of the three-axis turntable through the inertial sensor and sending the rotation data to the data acquisition computer; the modeling module is used for indicating the data acquisition computer to establish a sensor error model of the inertial sensor; and the analysis module is used for carrying out data analysis processing on the rotation data through a sensor error model to obtain parameter data and carrying out calibration processing on the inertial sensor according to the parameter data.

Optionally, the parsing module is further configured to: under the condition that the difference value between the rotation data and the parameter data is smaller than a preset threshold value, finishing the calibration processing; and under the condition that the difference value between the rotation data and the parameter data is larger than the preset threshold value, circularly executing the calibration processing step until the difference value between the rotation data and the parameter data is smaller than the preset threshold value.

According to yet another embodiment of the invention, there is also provided a computer-readable storage medium comprising a stored program, wherein the program when executed performs the method described in any of the above.

According to yet another embodiment of the present invention, there is also provided an electronic apparatus comprising a memory having a computer program stored therein and a processor arranged to perform the method described in any one of the above by means of the computer program.

According to the invention, the calibration processing step comprises the following steps: controlling the rotation of the three-axis turntable according to the turntable control information, wherein the turntable control information comprises: controlling the working mode and the rotation rate of a three-axis turntable set by a computer through the turntable; acquiring rotation data of the three-axis turntable through an inertial sensor, and sending the rotation data to a data acquisition computer; instructing the data acquisition computer to build a sensor error model of the inertial sensor; and carrying out data analysis processing on the rotation data through a sensor error model to obtain parameter data, and calibrating the inertial sensor according to the parameter data. That is to say, according to the technical scheme, the three-axis rotary table is controlled to rotate according to the rotary table control information, the rotation data of the three-axis rotary table is acquired through the inertial sensor, the rotation data is sent to the data acquisition computer, and the data acquisition computer is instructed to establish a sensor error model of the inertial sensor. And carrying out data analysis processing on the rotation data through a sensor error model to obtain parameter data, and calibrating the inertial sensor according to the parameter data. By adopting the technical scheme, the problem of poor calibration effect on the sensor in the related technology is solved, so that the accuracy of data acquisition of the sensor is improved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:

fig. 1 is a block diagram of a hardware structure of a computer terminal of a sensor calibration method according to an embodiment of the present invention;

FIG. 2 is a schematic flow chart diagram of a method for calibrating a sensor according to an embodiment of the present invention;

FIG. 3 is a flow chart of an automatic calibration of a sensor according to an embodiment of the present invention;

FIG. 4 is a flow chart of a sensor error compensation according to an embodiment of the present invention;

FIG. 5 is a schematic flow chart illustrating automatic calibration of a sensor according to an embodiment of the present invention;

FIG. 6 is a flow chart of a gyroscope calibration according to an embodiment of the present invention;

FIG. 7 is a flow chart of accelerometer calibration according to an embodiment of the invention;

fig. 8 is a block diagram of a sensor calibration apparatus according to an embodiment of the present invention.

Detailed Description

In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, 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. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.

It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

The method provided by the embodiment of the application can be executed in a computer terminal or a similar operation device. Taking the operation on a computer terminal as an example, fig. 1 is a hardware structure block diagram of a computer terminal of a sensor calibration method according to an embodiment of the present invention. As shown in fig. 1, the computer terminal may include one or more processors 102 (only one is shown in fig. 1), wherein the processors 102 may include, but are not limited to, a Microprocessor (MPU) or a Programmable Logic Device (PLD), and a memory 104 for storing data, and in an exemplary embodiment, the computer terminal may further include a transmission device 106 for communication function and an input/output device 108. It will be understood by those skilled in the art that the structure shown in fig. 1 is only an illustration and is not intended to limit the structure of the computer terminal. For example, the computer terminal may also include more or fewer components than shown in FIG. 1, or have a different configuration with equivalent functionality to that shown in FIG. 1 or with more functionality than that shown in FIG. 1.

The memory 104 can be used for storing computer programs, for example, software programs and modules of application software, such as computer programs corresponding to the sensor calibration method in the embodiment of the present invention, and the processor 102 executes various functional applications and data processing by running the computer programs stored in the memory 104, so as to implement the above-mentioned method. The memory 104 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory located remotely from the processor 102, which may be connected to a computer terminal over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The transmission device 106 is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the computer terminal. In one example, the transmission device 106 includes a Network adapter (NIC), which can be connected to other Network devices through a base station so as to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.

In this embodiment, a sensor calibration method is provided, and fig. 2 is a schematic flow chart of a sensor calibration method according to an embodiment of the present invention, where the sensor calibration method includes the following steps:

step S202: controlling the rotation of the three-axis turntable according to the turntable control information, wherein the turntable control information comprises: controlling the working mode and the rotation rate of a three-axis turntable set by a computer through the turntable;

step S204: acquiring rotation data of the three-axis turntable through an inertial sensor, and sending the rotation data to a data acquisition computer;

step S206: instructing the data acquisition computer to build a sensor error model of the inertial sensor;

step S208: and carrying out data analysis processing on the rotation data through a sensor error model to obtain parameter data, and calibrating the inertial sensor according to the parameter data.

According to the invention, the calibration processing step comprises the following steps: controlling the rotation of the three-axis turntable according to the turntable control information, wherein the turntable control information comprises: controlling the working mode and the rotation rate of a three-axis turntable set by a computer through the turntable; acquiring rotation data of the three-axis turntable through an inertial sensor, and sending the rotation data to a data acquisition computer; instructing the data acquisition computer to build a sensor error model of the inertial sensor; and carrying out data analysis processing on the rotation data through a sensor error model to obtain parameter data, and calibrating the inertial sensor according to the parameter data. That is to say, according to the technical scheme, the three-axis rotary table is controlled to rotate according to the rotary table control information, the rotation data of the three-axis rotary table is acquired through the inertial sensor, the rotation data is sent to the data acquisition computer, and the data acquisition computer is instructed to establish a sensor error model of the inertial sensor. And carrying out data analysis processing on the rotation data through a sensor error model to obtain parameter data, and calibrating the inertial sensor according to the parameter data. By adopting the technical scheme, the problem of poor calibration effect on the sensor in the related technology is solved, so that the accuracy of data acquisition of the sensor is improved.

After step S208, that is, after the inertial sensor is calibrated according to the parameter data, if the difference between the rotation data and the parameter data is smaller than a preset threshold, the calibration process is ended; and under the condition that the difference value between the rotation data and the parameter data is larger than the preset threshold value, circularly executing the calibration processing step until the difference value between the rotation data and the parameter data is smaller than the preset threshold value.

That is, the calibration process for the inertial sensor includes: calibrating the inertial sensor for the first time according to the steps S202-S208; under the condition that the difference value between the rotation data and the parameter data is smaller than a preset threshold value, finishing the calibration processing of the inertial sensor; and under the condition that the difference value between the rotation data and the parameter data is greater than the preset threshold value, circularly executing the step S202 to the step S208 until the difference value between the rotation data and the parameter data is less than the preset threshold value, and finishing the calibration processing of the inertial sensor. The problem of poor calibration effect on the sensor in the related technology is solved by repeatedly calibrating the inertial sensor, so that the accuracy of data acquisition of the sensor is improved.

In an alternative embodiment, the data analysis processing of the rotation data by the sensor error model includes: in a case where the sensor error model includes a gyroscope error model, determining the following gyroscope equation as the gyroscope error model: u- ω₀+K_gω, u is the output of the gyroscope, w₀Is the zero bias of the gyroscope, ω is the input of the gyroscope, K_gA scale factor of the gyroscope; and inputting the rotation data into the gyroscope formula so as to analyze and process the rotation data.

It should be noted that, determining a gyroscope formula as the gyroscope error model actually determines a matrix form of the gyroscope formula as the gyroscope error model, where the gyroscope formula: u- ω 0+ Kg ω in matrix form:

wherein u is_x，u_y，u_zValues of the output u of the gyroscope in the x-axis, the y-axis and the z-axis respectively; omega_0x，ω_0y，ω_0zIs zero offset w of a gyroscope₀Values in the x, y and z axes, respectively; omega_x，ω_y，ω_zValues of the input omega of the gyroscope in the x-axis, the y-axis and the z-axis respectively; k_gx，K_gy，K_gzScale factor K for a gyroscope_gValues on the x, y and z axes, respectively.

In an alternative embodiment, the data analysis processing of the rotation data by the sensor error model includes: in case the sensor error model comprises an accelerometer error model, the following will beAnd determining an acceleration formula as the accelerometer error model: a is₀+K_aa, f are the output of the accelerometer, a₀Is the zero offset of the accelerometer, a is the input of the accelerometer, K_aIs a scale factor of the accelerometer; and inputting the rotation data into the acceleration formula to perform data analysis processing on the rotation data.

It should be noted that, the accelerometer formula is determined as the accelerometer error model, and actually, the matrix form of the accelerometer formula is determined as the accelerometer error model, where the accelerometer formula: a is₀+K_aMatrix form of a:

wherein f is_x，f_y，f_zValues of the output f of the accelerometer in the x-axis, the y-axis and the z-axis respectively; a is_0x，a_0y，a_0zIs zero offset a of accelerometer₀Values in the x, y and z axes, respectively; a is_x，a_y，a_zIs the value of the input a of the accelerometer in the x-axis, the y-axis and the z-axis respectively; k_ax，K_ay，K_azAs scale factor K of the accelerometer_aValues on the x, y and z axes, respectively.

In an optional embodiment, performing data analysis processing on the rotation data through a sensor error model to obtain parameter data, and performing calibration processing on the inertial sensor according to the parameter data includes: inputting the rotation data into the gyroscope error model to obtain gyroscope output data; and under the condition that the inertial sensor comprises a gyroscope, calibrating the gyroscope according to the output data of the gyroscope.

It should be noted that the rotation data is input into the gyroscope error model to obtain gyroscope output data, where the parameter data includes gyroscope output data, and the gyroscope is calibrated according to the gyroscope output data, where the inertial sensor includes a gyroscope.

In an optional embodiment, performing data analysis processing on the rotation data through a sensor error model to obtain parameter data, and performing calibration processing on the inertial sensor according to the parameter data includes: inputting the rotation data into the accelerometer error model to obtain acceleration output data; and under the condition that the inertial sensor comprises an accelerometer, calibrating the accelerometer according to the acceleration output data.

The rotation data is input into the accelerometer error model to obtain acceleration output data, wherein the parameter data comprises the acceleration output data; and calibrating the accelerometer according to the acceleration output data, wherein the inertial sensor comprises an accelerometer.

And solving parameters in the accelerometer error model and the gyroscope error model according to the acquired data, wherein a least square method is adopted in the optional embodiment of the invention.

Recording the data measurement as y_iEstimated value of model calculationAn error ofSquare deviationMinimum as criterion (i.e. least square criterion) for determining the parameter to be determinedAndthe method of (2) is called the least squares method. Expressed by formula, the least squares method satisfies the following least squares criterion:

given a set of test data, (x)_i,y_i) Is known, andandare temporarily unknown, they are not considered as unknown variables at this time, so Q isAndis used as a binary function of (1). According to the extreme value theory of the multivariate function, the minimum value of Q must be taken in the Q pairAndat a stationary point where the partial derivative of (A) is zero, i.e. a parameter to be determinedAndthe requirements are as follows:

the above equation is often referred to as a normal system of equations, and the solution can be obtained:

given a certain set of test data, the unknown parameters in the accelerometer error model and the gyroscope error model can be solved.

In an alternative embodiment, the sensor of the present invention may be a MEMS-IMU sensor. The MEMS inertial measurement unit consists of three accelerometers and three MEMS gyroscopes, and parameters of the MEMS inertial components can be divided into dynamic parameters, static parameters, time-varying parameters, temperature-varying parameters and the like. Taking a traditional error model as an example, only static parameters of the MEMS inertial measurement unit are considered during discrete error calibration, only zero-order and first-order parameters of the MEMS inertial measurement unit are considered, and installation errors are not considered, and the MEMS inertial measurement unit mainly comprises zero offset and scale factors of the MEMS gyroscope and the accelerometer.

In order to better understand the above technical solution, the following optional flowchart is used to explain the whole process of the sensor calibration method.

FIG. 3 is a flow chart of automatic calibration of a sensor according to an embodiment of the present invention, as shown in FIG. 3:

the automatic calibration device consists of four parts: a turntable control computer, a turntable driver, a three-axis turntable and a high-performance computer. Firstly, the working mode and the speed of the rotary table are set through the rotary table control computer, the rotary table driver enables the three-axis rotary table to operate after receiving the information, the high-performance computer collects data output by the rotary table through a communication protocol (taking RS-422 as an example), a corresponding error model (namely a sensor error model) is established, the corresponding parameters are solved through an algorithm, and then the parameters are returned to the sensor through the communication protocol. After the data are sent to the sensor, the parameters need to be verified, at this time, the working mode and the speed of the rotary table are set through the rotary table control computer, and after the three-axis rotary table operates, whether the data in the data list are consistent with the set parameters or not is observed, and whether a large error exists or not is observed. If the error is very small, the calibration is successful; otherwise, the steps are repeated.

FIG. 4 is a flow chart of sensor error compensation according to an embodiment of the present invention, as shown in FIG. 4:

the error compensation of the MEMS inertial measurement unit is to establish a compensation model according to the difference between the input U and the output U of the MEMS inertial measurement unit, compensate the output data of the accelerometer by utilizing the established error compensation model, and obtain the compensated output result U'.

Fig. 5 is a schematic flow chart of automatic calibration of a sensor according to an embodiment of the present invention, as shown in fig. 5:

s502: respectively acquiring output data of the MEMS gyroscope under different speed rotation when three sensitive axes of the MEMS gyroscope are vertical to an inner frame (ground) through an uncalibrated MEMS gyroscope;

s504: respectively acquiring output data of the MEMS accelerometer when three sensitive axes are vertical to the ground direction through the uncalibrated accelerometer;

s506: and establishing a sensor error model of the MEMS inertial device for the output data, solving zero offset and scale factors of the MEMS gyroscope and the accelerometer, fitting the error of the MEMS inertial device according to the sensor error model for solving the zero offset and scale factors, and quickly calibrating the MEMS inertial device according to the error. The calibration of the MEMS inertial device is to calibrate the MEMS gyroscope by utilizing the angular velocity induced by the MEMS gyroscope and the angular velocity of the rotation of the output shaft of the three-axis turntable and the rotating speed of the inner frame of the three-axis turntable; the MEMS accelerometer is calibrated by sensing the gravity acceleration g by the MEMS accelerometer, and is calibrated by the static state of the inner frame (shock insulation table) of the three-cycle turntable.

FIG. 6 is a flowchart of a gyroscope calibration according to an embodiment of the invention, as shown in FIG. 6:

s602: locking an outer frame and a middle frame of the three-circle turntable at an initial position, and enabling an input reference shaft of the MEMS gyroscope to be in a horizontal position vertical to the inner frame through a tool;

s604: the turntable is electrified, only the inner frame is rotated, and the speed rates of the inner frame are respectively 1000, 500, 200, 0, (-200), (-500), (-1000). (wherein each rotational speed is maintained for 10s, in the above units of °/s);

s606: storing the collected data information in a text;

s608: repeating the steps S602-S606 to obtain output data of the MEMS gyroscope in three axial directions;

s610: and (3) using an MEMS automatic calibration program, opening recorded data, solving the zero offset and the scale factor of the gyroscope through the program, and sending the two parameters back to the MEMS gyroscope to realize the calibration of the gyroscope.

FIG. 7 is a flow chart of accelerometer calibration according to an embodiment of the invention, as shown in FIG. 7:

s702: at an initial position, an input reference shaft of the MEMS accelerometer is vertical to an inner frame (ground) of the shock insulation table or the three-axis turntable through a tool;

s704: respectively keeping the MEMS accelerometers at 9.8m/s²、0m/s²、(-9.8m/s²) Each held stationary for 10 s;

s706: storing the collected data information in a text;

s708: repeating the steps S702-S706 to obtain the output data of the MEMS accelerometer in three axial directions;

s710: and (3) using an MEMS automatic calibration program, opening recorded data, solving the zero offset and the scale factor of the accelerometer through the program, and sending the two parameters back to the MEMS accelerometer to realize the calibration of the accelerometer.

According to the invention, the calibration processing step comprises the following steps: controlling the rotation of the three-axis turntable according to the turntable control information, wherein the turntable control information comprises: controlling the working mode and the rotation rate of a three-axis turntable set by a computer through the turntable; acquiring rotation data of the three-axis turntable through an inertial sensor, and sending the rotation data to a data acquisition computer; instructing the data acquisition computer to build a sensor error model of the inertial sensor; and carrying out data analysis processing on the rotation data through a sensor error model to obtain parameter data, and calibrating the inertial sensor according to the parameter data. That is to say, according to the technical scheme, the three-axis rotary table is controlled to rotate according to the rotary table control information, the rotation data of the three-axis rotary table is acquired through the inertial sensor, the rotation data is sent to the data acquisition computer, and the data acquisition computer is instructed to establish a sensor error model of the inertial sensor. And carrying out data analysis processing on the rotation data through a sensor error model to obtain parameter data, and calibrating the inertial sensor according to the parameter data. By adopting the technical scheme, the problem of poor calibration effect on the sensor in the related technology is solved, so that the accuracy of data acquisition of the sensor is improved.

Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.

The present embodiment further provides a sensor calibration apparatus, which is used to implement the foregoing embodiments and preferred embodiments, and the description of the apparatus is omitted for brevity. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.

Fig. 8 is a block diagram of a sensor calibration apparatus according to an embodiment of the present invention, including:

a control module 80, configured to control rotation of the three-axis turntable according to turntable control information, where the turntable control information includes: controlling the working mode and the rotation rate of a three-axis turntable set by a computer through the turntable;

the acquisition module 82 is used for acquiring the rotation data of the three-axis turntable through an inertial sensor and sending the rotation data to a data acquisition computer;

a modeling module 84 for instructing the data acquisition computer to model sensor errors of the inertial sensors in accordance with the established sensor error model;

and the analysis module 86 is used for performing data analysis processing on the rotation data through a sensor error model to obtain parameter data, and calibrating the inertial sensor according to the parameter data.

According to the invention, the rotation of the three-axis turntable is controlled according to the turntable control information, wherein the turntable control information comprises: controlling the working mode and the rotation rate of a three-axis turntable set by a computer through the turntable; acquiring rotation data of the three-axis turntable through an inertial sensor, and sending the rotation data to a data acquisition computer; instructing the data acquisition computer to build a sensor error model of the inertial sensor; and carrying out data analysis processing on the rotation data through a sensor error model to obtain parameter data, and calibrating the inertial sensor according to the parameter data. That is to say, according to the technical scheme, the three-axis rotary table is controlled to rotate according to the rotary table control information, the rotation data of the three-axis rotary table is acquired through the inertial sensor, the rotation data is sent to the data acquisition computer, and the data acquisition computer is instructed to establish a sensor error model of the inertial sensor. And carrying out data analysis processing on the rotation data through a sensor error model to obtain parameter data, and calibrating the inertial sensor according to the parameter data. By adopting the technical scheme, the problem of poor calibration effect on the sensor in the related technology is solved, so that the accuracy of data acquisition of the sensor is improved.

Optionally, the analysis module 86 is further configured to end the calibration processing when a difference between the rotation data and the parameter data is smaller than a preset threshold; and under the condition that the difference value between the rotation data and the parameter data is larger than the preset threshold value, circularly executing the calibration processing step until the difference value between the rotation data and the parameter data is smaller than the preset threshold value.

That is, the calibration process for the inertial sensor includes: calibrating the inertial sensor for the first time according to the steps S202-S208; under the condition that the difference value between the rotation data and the parameter data is smaller than a preset threshold value, finishing the calibration processing of the inertial sensor; and under the condition that the difference value between the rotation data and the parameter data is greater than the preset threshold value, circularly executing the step S202 to the step S208 until the difference value between the rotation data and the parameter data is less than the preset threshold value, and finishing the calibration processing of the inertial sensor. The problem of poor calibration effect on the sensor in the related technology is solved by repeatedly calibrating the inertial sensor, so that the accuracy of data acquisition of the sensor is improved.

Optionally, the parsing module 86 is further configured to determine, as the gyroscope error model, the following gyroscope formula in a case that the sensor error model includes the gyroscope error model: u- ω₀+K_gω, u is the output of the gyroscope, w₀Is the zero bias of the gyroscope, ω is the input of the gyroscope, K_gA scale factor of the gyroscope; and inputting the rotation data into the gyroscope formula so as to analyze and process the rotation data.

It should be noted that, determining a gyroscope formula as the gyroscope error model actually determines a matrix form of the gyroscope formula as the gyroscope error model, where the gyroscope formula: u- ω 0+ Kg ω in matrix form:

wherein u is_x，u_y，u_zValues of the output u of the gyroscope in the x-axis, the y-axis and the z-axis respectively; omega_0x，ω_0y，ω_0zIs zero offset w of a gyroscope₀Values in the x, y and z axes, respectively; omega_x，ω_y，ω_zValues of the input omega of the gyroscope in the x-axis, the y-axis and the z-axis respectively; k_gx，K_gy，K_gzScale factor K for a gyroscope_gValues on the x, y and z axes, respectively.

Optionally, the analysis module 86 is further configured to analyze the sensor error modelIn the case where the model includes an accelerometer error model, the following acceleration equation is determined as the accelerometer error model: a is₀+K_aa, f are the output of the accelerometer, a₀Is the zero offset of the accelerometer, a is the input of the accelerometer, K_aIs a scale factor of the accelerometer; and inputting the rotation data into the acceleration formula to perform data analysis processing on the rotation data.

It should be noted that, the accelerometer formula is determined as the accelerometer error model, and actually, the matrix form of the accelerometer formula is determined as the accelerometer error model, where the accelerometer formula: a is₀+K_aMatrix form of a:

wherein f is_x，f_y，f_zValues of the output f of the accelerometer in the x-axis, the y-axis and the z-axis respectively; a is_0x，a_0y，a_0zIs zero offset a of accelerometer₀Values in the x, y and z axes, respectively; a is_x，a_y，a_zIs the value of the input a of the accelerometer in the x-axis, the y-axis and the z-axis respectively; k_ax，K_ay，K_azAs scale factor K of the accelerometer_aValues on the x, y and z axes, respectively.

Optionally, the analysis module 86 is further configured to input the rotation data into the gyroscope error model to obtain gyroscope output data; and under the condition that the inertial sensor comprises a gyroscope, calibrating the gyroscope according to the output data of the gyroscope.

It should be noted that the rotation data is input into the gyroscope error model to obtain gyroscope output data, where the parameter data includes gyroscope output data, and the gyroscope is calibrated according to the gyroscope output data, where the inertial sensor includes a gyroscope.

Optionally, the analysis module 86 is further configured to input the rotation data into the accelerometer error model to obtain acceleration output data; and under the condition that the inertial sensor comprises an accelerometer, calibrating the accelerometer according to the acceleration output data.

The rotation data is input into the accelerometer error model to obtain acceleration output data, wherein the parameter data comprises the acceleration output data; and calibrating the accelerometer according to the acceleration output data, wherein the inertial sensor comprises an accelerometer.

And solving parameters in the accelerometer error model and the gyroscope error model according to the acquired data, wherein a least square method is adopted in the optional embodiment of the invention.

Recording the data measurement as y_iEstimated value of model calculationAn error ofSquare deviationMinimum as criterion (i.e. least square criterion) for determining the parameter to be determinedAndthe method of (2) is called the least squares method. Expressed by formula, the least squares method satisfies the following least squares criterion:

given a set of test data, (x)_i,y_i) Is known, andandare temporarily unknown, they are not considered as unknown variables at this time, so Q isAndis used as a binary function of (1). According to the extreme value theory of the multivariate function, the minimum value of Q must be taken in the Q pairAndat a stationary point where the partial derivative of (A) is zero, i.e. a parameter to be determinedAndthe requirements are as follows:

the above equation is often referred to as a normal system of equations, and the solution can be obtained:

given a certain set of test data, the unknown parameters in the accelerometer error model and the gyroscope error model can be solved.

In an alternative embodiment, the sensor of the present invention may be a MEMS-IMU sensor. The MEMS inertial measurement unit consists of three accelerometers and three MEMS gyroscopes, and parameters of the MEMS inertial components can be divided into dynamic parameters, static parameters, time-varying parameters, temperature-varying parameters and the like. Taking a traditional error model as an example, only static parameters of the MEMS inertial measurement unit are considered during discrete error calibration, only zero-order and first-order parameters of the MEMS inertial measurement unit are considered, and installation errors are not considered, and the MEMS inertial measurement unit mainly comprises zero offset and scale factors of the MEMS gyroscope and the accelerometer.

It should be noted that, the above modules may be implemented by software or hardware, and for the latter, the following may be implemented, but not limited to: the modules are all positioned in the same processor; alternatively, the modules are respectively located in different processors in any combination.

Embodiments of the present invention also provide a storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the above method embodiments when executed.

Alternatively, in the present embodiment, the storage medium may be configured to store a computer program for executing the steps of:

s1, controlling the rotation of the three-axis turntable according to the turntable control information, wherein the turntable control information comprises: controlling the working mode and the rotation rate of a three-axis turntable set by a computer through the turntable;

s2, acquiring rotation data of the three-axis turntable through an inertial sensor, and sending the rotation data to a data acquisition computer;

s3, instructing the data acquisition computer to establish a sensor error model of the inertial sensor;

and S4, performing data analysis processing on the rotation data through a sensor error model to obtain parameter data, and calibrating the inertial sensor according to the parameter data.

Optionally, in this embodiment, the storage medium may include, but is not limited to: various media capable of storing computer programs, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.

Embodiments of the present invention also provide an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the above method embodiments.

Optionally, the electronic apparatus may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.

Optionally, in this embodiment, the processor may be configured to execute the following steps by a computer program:

s1, controlling the rotation of the three-axis turntable according to the turntable control information, wherein the turntable control information comprises: controlling the working mode and the rotation rate of a three-axis turntable set by a computer through the turntable;

s2, acquiring rotation data of the three-axis turntable through an inertial sensor, and sending the rotation data to a data acquisition computer;

s3, instructing the data acquisition computer to establish a sensor error model of the inertial sensor;

and S4, performing data analysis processing on the rotation data through a sensor error model to obtain parameter data, and calibrating the inertial sensor according to the parameter data.

Optionally, in this option, the specific examples in this embodiment may refer to the examples described in the foregoing embodiment and optional implementation, and this embodiment is not described herein again.

It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.

The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the principle of the present invention should be included in the protection scope of the present invention.