A method, device, computing equipment and storage medium for correcting temperature drift of MEMS gyroscope

Abstract

The present application provides a method, device, computing device and storage medium for correcting the temperature drift of a MEMS gyroscope. Among them, the temperature value of the MEMS gyroscope in each sampling period is recorded by a built-in temperature sensor; a nonlinear influence factor is calculated based on the temperature value, the acquisition time and the operating frequency of the MEMS gyroscope, and the nonlinear influence factor is used to balance the influence of the temperature value, the time and the operating frequency on the output signal of the MEMS gyroscope; a multivariable dynamic compensation algorithm is used to correct the output signal of the MEMS gyroscope based on the nonlinear influence factor to minimize the drift error caused by temperature changes. The technical solution provided by the present application effectively improves the correction effect of the MEMS gyroscope.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of data correction technology, and in particular to a method, apparatus, computing device, and storage medium for correcting temperature drift of a MEMS gyroscope. Background Art

[0002] With the development of MEMS (Micro-Electro-Mechanical System) technology, MEMS gyroscopes have been widely used in navigation, attitude control, consumer electronics and other fields due to their small size, light weight and low cost. However, MEMS gyroscopes will show different degrees of temperature drift under different ambient temperatures, which poses a challenge to the accuracy and stability of the system. Especially in high-precision application scenarios such as aerospace, autonomous driving, and drone control, temperature drift may seriously affect the navigation accuracy and reliability of the system. Therefore, a method that can effectively correct temperature drift is needed to meet the needs of these fields for high-precision attitude measurement.

[0003] At present, the correction method for temperature drift of MEMS gyroscopes is mainly achieved through static calibration or simple temperature compensation algorithms. These methods usually compensate based on the relationship curve between pre-measured temperature and output signal, or use linear models to approximate nonlinear temperature effects. Although these methods can improve the temperature drift problem to a certain extent, they often fail to fully consider the impact of dynamic factors such as temperature change rate and operating frequency on the output signal, so the correction effect is limited. Summary of the invention

[0004] The embodiments of the present application provide a method, apparatus, computing device and storage medium for correcting the temperature drift of a MEMS gyroscope, so as to solve the problem of poor correction effect in the prior art.

[0005] In a first aspect, an embodiment of the present application provides a method for correcting temperature drift of a MEMS gyroscope, comprising:

[0006] The temperature value of the MEMS gyroscope in each sampling period is recorded through the built-in temperature sensor;

[0007] Calculating a nonlinear impact factor according to the temperature value, the acquired time, and the operating frequency of the MEMS gyroscope, wherein the nonlinear impact factor is used to balance the influence of the temperature value, the time, and the operating frequency on the output signal of the MEMS gyroscope;

[0008] A multivariable dynamic compensation algorithm is used to correct the output signal of the MEMS gyroscope according to the nonlinear influencing factors to minimize the drift error caused by temperature changes.

[0009] Optionally, it also includes:

[0010] Using adaptive filtering technology to monitor the output signal changes of the MEMS gyroscope in real time;

[0011] The change of the output signal is compared with the ideal output signal, and based on the comparison result, the nonlinear impact factor is dynamically adjusted to correct the output signal of the MEMS gyroscope.

[0012] Optionally, it also includes:

[0013] Measuring the dynamic response characteristics of the MEMS gyroscope at different temperatures to obtain measurement results;

[0014] The nonlinear impact factor is adjusted according to the measurement result to correct the output signal of the MEMS gyroscope.

[0015] Optionally, the method further includes: adjusting the temperature gradient in the nonlinear influencing factor according to monitoring the ambient temperature change of the operating environment of the MEMS gyroscope to correct the output signal of the MEMS gyroscope.

[0016] Optionally, the nonlinear impact factor It is defined by the following formula:

[0017] ;

[0018] in, is the temperature value, For time, is the operating frequency, is the reference frequency, are constants determined experimentally, represents the temperature gradient, is the time-dependent phase shift function, the integral term Represents the cumulative effect of the temperature gradient from the initial moment to the current moment.

[0019] Optionally, the correcting the output signal of the MEMS gyroscope according to the nonlinear impact factor includes:

[0020] The output signal of the MEMS gyroscope is corrected according to the nonlinear influence factor by the following formula:

[0021] ;

[0022] in, is the corrected output signal, is the original output signal, that is, the uncorrected MEMS gyroscope output signal, is the nonlinear influencing factor, For the ideal output signal, and is a predetermined amplitude and initial phase angle, is the angular frequency, usually associated with the frequency of oscillation, is the coefficient related to the frequency change rate, is the frequency change rate, and is an additional modulation parameter related to time.

[0023] Optionally, the frequency change rate The calculation formula is as follows:

[0024] ;

[0025] in, is a constant determined experimentally, is the rate of change of the operating frequency over time, indicating the change of the operating frequency per unit time. is the rate of change of temperature over time, indicating the rate of temperature change, Indicates the operating frequency With reference frequency The ratio between is the time-dependent phase shift function.

[0026] In a second aspect, an embodiment of the present application provides a device for correcting temperature drift of a MEMS gyroscope, comprising:

[0027] A recording module is used to record the temperature value of the MEMS gyroscope in each sampling period through a built-in temperature sensor;

[0028] A calculation module, used to calculate a nonlinear influence factor according to the temperature value, the acquired time and the operating frequency of the MEMS gyroscope, wherein the nonlinear influence factor is used to balance the influence of the temperature value, the time and the operating frequency on the output signal of the MEMS gyroscope;

[0029] The correction module is used to correct the output signal of the MEMS gyroscope according to the nonlinear influencing factor by adopting a multivariable dynamic compensation algorithm to minimize the drift error caused by temperature change.

[0030] In a third aspect, an embodiment of the present application provides a computing device, comprising a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a method for correcting temperature drift of a MEMS gyroscope as described in any one of the first aspects.

[0031] In a fourth aspect, an embodiment of the present application provides a computer storage medium storing a computer program, wherein when the computer program is executed by a computer, a method for correcting temperature drift of a MEMS gyroscope as described in any one of the first aspects is implemented.

[0032] In the embodiment of the present application, the temperature value of the MEMS gyroscope in each sampling period is recorded by a built-in temperature sensor; the nonlinear influence factor is calculated according to the temperature value, the acquisition time and the operating frequency of the MEMS gyroscope, and the nonlinear influence factor is used to balance the influence of the temperature value, the time and the operating frequency on the output signal of the MEMS gyroscope; a multivariable dynamic compensation algorithm is used to correct the output signal of the MEMS gyroscope according to the nonlinear influence factor to minimize the drift error caused by temperature changes. The technical solution provided by the present application ensures that the MEMS gyroscope can work stably and reliably in various environments.

[0033] These and other aspects of the present application will become more clearly understood in the description of the following embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0035] Figure 1 A flow chart of a method for correcting temperature drift of a MEMS gyroscope provided in an embodiment of the present application;

[0036] Figure 2 A schematic diagram of the structure of a device for correcting temperature drift of a MEMS gyroscope provided in an embodiment of the present application;

[0037] Figure 3 A schematic diagram of the structure of a computing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0038] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0039] In some of the processes described in the specification and claims of this application and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this article or executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish between different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., do not represent the order of precedence, and do not limit the "first" and "second" to be different types.

[0040] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0041] Figure 1 A flowchart of a method for correcting temperature drift of a MEMS gyroscope is provided for an embodiment of the present application, such as Figure 1 As shown, the method includes:

[0042] 101. Record the temperature value of the MEMS gyroscope in each sampling period through the built-in temperature sensor;

[0043] In this step, the temperature value of the MEMS gyroscope in each sampling period is recorded through the built-in temperature sensor. The concepts involved here include:

[0044] Built-in temperature sensor: This is a temperature detection element installed inside the MEMS gyroscope, which is used to monitor the temperature changes of the gyroscope's working environment in real time. The built-in temperature sensor is usually a semiconductor sensor that can convert temperature changes into electrical signal output.

[0045] Sampling period: refers to the time interval at which the temperature sensor collects temperature data. During one sampling period, the sensor reads the temperature value once. The selection of the sampling period depends on the required resolution and real-time requirements.

[0046] Temperature value: The temperature data read by the temperature sensor, usually expressed in degrees Celsius (°C) or Kelvin (K). These temperature values ​​are important inputs to the subsequent temperature drift correction algorithm.

[0047] In the embodiment of the present application, a built-in temperature sensor (Temperature Sensor, TS) is integrated inside the MEMS gyroscope to achieve real-time monitoring of the working environment temperature of the gyroscope. For example, assume that a typical MEMS gyroscope has a highly sensitive semiconductor temperature sensor integrated inside, and the sensor collects temperature data every 1 second.

[0048] The specific embodiments are as follows:

[0049] Integration of built-in temperature sensor: The temperature sensor integrated inside the MEMS gyroscope is TMP102 (Temperature Monitor 102, TMP102), which has the characteristics of high accuracy and fast response. TMP102 is connected to the control circuit of the MEMS gyroscope through the I²C interface.

[0050] Sampling cycle setting: In order to ensure the real-time and accuracy of temperature data, a sampling frequency of once per second (1Hz) is set. This means that the temperature sensor reads the current ambient temperature once every 1 second and transmits the reading to the data processing module of the MEMS gyroscope.

[0051] Temperature value recording: Assume that in a specific operating scenario, after the MEMS gyroscope is started, the built-in temperature sensor starts working. In the first sampling cycle, the temperature sensor reads a temperature value of 25°C. As the ambient temperature changes, the temperature value may be different in subsequent sampling cycles. For example, in the second sampling cycle, the temperature sensor reads a temperature value of 25.2°C.

[0052] Application of temperature data: These temperature values ​​are then used to calculate the nonlinear influence factor (NIF). For example, the nonlinear influence factor The calculation of is as follows:

[0053] ;

[0054] in, is the current temperature value (e.g. 25°C), is the time (e.g. 1 second), is the operating frequency (e.g. 100 Hz), is the exponential function part, which represents the influence of temperature TT on the nonlinear influencing factor. is the base frequency (e.g. 1000Hz), is the time-dependent phase shift function, is the rate of change of temperature with time.

[0055] In this specific embodiment, the built-in temperature sensor TMP102 records the temperature value inside the MEMS gyroscope every 1 second and transmits these temperature values ​​to the data processing module through the I²C interface. The data processing module calculates the nonlinear influence factor based on these temperature values, thereby providing necessary data support for subsequent temperature drift correction.

[0056] 102. Calculate a nonlinear impact factor according to the temperature value, the acquired time, and the operating frequency of the MEMS gyroscope, wherein the nonlinear impact factor is used to balance the influence of the temperature value, the time, and the operating frequency on the output signal of the MEMS gyroscope;

[0057] Optionally, the nonlinear impact factor in step 102 is It is defined by the following formula:

[0058] ;

[0059] in, is the temperature value, For time, is the operating frequency, is the reference frequency, are constants determined experimentally, represents the temperature gradient, is the time-dependent phase shift function, the integral term Represents the cumulative effect of the temperature gradient from the initial moment to the current moment.

[0060] In this step, a nonlinear influence factor is calculated by using the temperature value, the acquired time, and the operating frequency of the MEMS gyroscope, and the nonlinear influence factor is used to balance the influence of the temperature value, the time, and the operating frequency on the output signal of the MEMS gyroscope. The concepts involved here include:

[0061] Nonlinear impact factor: This is a factor that combines the effects of three variables: temperature, time, and operating frequency. It is used to evaluate and balance the impact of these factors on the output signal of the MEMS gyroscope.

[0062] Temperature value: The current ambient temperature measured by the built-in temperature sensor.

[0063] Time: refers to the moment within the sampling period, which is used to track the process of temperature change.

[0064] Operating frequency: The operating frequency of the MEMS gyroscope reflects how fast it works.

[0065] Base frequency: used as a reference frequency value to standardize the frequency measurement.

[0066] Temperature gradient: represents the rate at which temperature changes over space and is used to evaluate changes in the temperature field.

[0067] Phase shift function: A time-dependent function used to describe the phase effect caused by temperature changes.

[0068] In the embodiment of the present application, the nonlinear impact factor It is defined by the following formula:

[0069] ;

[0070] in, is the temperature value, For time, is the operating frequency, The reference frequency are constants determined experimentally, represents the temperature gradient, is the time-dependent phase shift function, the integral term Represents the cumulative effect of the temperature gradient from the initial moment to the current moment.

[0071] The specific embodiments are as follows:

[0072] Suppose in an experiment, the temperature sensor inside the MEMS gyroscope measures the current temperature T =25°C, current time is Seconds, the operating frequency of the MEMS gyroscope , reference frequency The constant values ​​determined experimentally are , , , , , , . Phase shift function Set as .

[0073] Temperature gradient Assuming the temperature rises by 0.1°C / m per second, The cumulative effect of the temperature gradient from the initial moment to the current moment is .

[0074] Substitute the above values ​​to calculate the nonlinear impact factor :

[0075] ;

[0076] Through the above calculations, we obtain the nonlinear impact factor The specific value of provides key data for subsequent temperature drift correction.

[0077] 103. Using a multivariable dynamic compensation algorithm, the output signal of the MEMS gyroscope is corrected according to the nonlinear influencing factor to minimize the drift error caused by temperature change.

[0078] Optionally, the step of correcting the output signal of the MEMS gyroscope according to the nonlinear impact factor in step 103 includes:

[0079] The output signal of the MEMS gyroscope is corrected according to the nonlinear influence factor by the following formula:

[0080] ;

[0081] in, is the corrected output signal, is the original output signal, that is, the uncorrected MEMS gyroscope output signal, is the nonlinear influencing factor, For the ideal output signal, and is a predetermined amplitude and initial phase angle, is the angular frequency, usually associated with the frequency of oscillation, is the coefficient related to the frequency change rate, is the frequency change rate, and is an additional modulation parameter related to time.

[0082] Optionally, the frequency change rate in step 103 is The calculation formula is as follows:

[0083] ;

[0084] in, is a constant determined experimentally, is the rate of change of the operating frequency over time, indicating the change of the operating frequency per unit time. is the rate of change of temperature over time, indicating the rate of temperature change, Indicates the operating frequency With reference frequency The ratio between is the time-dependent phase shift function.

[0085] In this step, a multivariable dynamic compensation algorithm is used to correct the output signal of the MEMS gyroscope according to the nonlinear influencing factors to minimize the drift error caused by temperature changes. The concepts involved here include:

[0086] Multivariable dynamic compensation algorithm: This is a dynamic adjustment algorithm based on multiple input variables (such as temperature, time, frequency, etc.), which aims to correct the output signal of the MEMS gyroscope in real time to make it as close to the ideal state as possible.

[0087] Nonlinear impact factor: A factor calculated by the previous steps to measure the impact of temperature, time and frequency changes on the output signal.

[0088] Corrected output signal: The output signal of the MEMS gyroscope after correction of nonlinear influence factors is theoretically closer to the true value.

[0089] Ideal output signal: Under ideal conditions, the signal value that the MEMS gyroscope should output is used to compare with the actual output signal to guide the correction process.

[0090] Amplitude and initial phase angle: used to adjust the intensity and initial phase of the correction signal.

[0091] Angular frequency: Associated with the frequency of oscillation, often used to represent the frequency of an oscillating signal.

[0092] Frequency change rate: Indicates the change in operating frequency per unit time, used to capture the trend of frequency changes over time.

[0093] Additional time-dependent modulation parameters: used to further modulate the output signal to better adapt to different environmental conditions.

[0094] In the embodiment of the present application, the output signal of the MEMS gyroscope is corrected according to the nonlinear influence factor, including correction by the following formula:

[0095] ;

[0096] in, is the corrected output signal, is the original output signal, that is, the uncorrected MEMS gyroscope output signal, is the nonlinear influencing factor, For the ideal output signal, and is a predetermined amplitude and initial phase angle, is the angular frequency, usually associated with the frequency of oscillation, is the coefficient related to the frequency change rate, is the frequency change rate, and is an additional modulation parameter related to time.

[0097] In addition, the frequency change rate The calculation formula is as follows:

[0098] ;

[0099] in, is a constant determined experimentally, is the rate of change of the operating frequency over time, indicating the change of the operating frequency per unit time. is the rate of change of temperature over time, indicating the rate of temperature change, Indicates the operating frequency With reference frequency The ratio between is the time-dependent phase shift function.

[0100] The specific embodiments are as follows:

[0101] Assume that in a specific application scenario, the original output signal of the MEMS gyroscope is , nonlinear impact factor , ideal output signal , amplitude , initial phase angle , angular frequency (i.e. 1Hz), the coefficient related to the frequency change rate The frequency change rate is , an additional modulation parameter related to time , phase angle .

[0102] Substituting the above values, calculate the corrected output signal :

[0103] ;

[0104] Assume the current time is seconds, then:

[0105] ;

[0106] Through the above calculation, we get the corrected output signal , which shows that the output signal after the nonlinear influence factor correction is closer to the ideal output signal, thus minimizing the drift error caused by temperature change.

[0107] Optionally, it also includes: using adaptive filtering technology to monitor the output signal changes of the MEMS gyroscope in real time; comparing the output signal changes with the ideal output signal, and based on the comparison result, dynamically adjusting the nonlinear impact factor to correct the output signal of the MEMS gyroscope.

[0108] In this step, adaptive filtering technology is used to monitor the output signal change of the MEMS gyroscope in real time, and the output signal change is compared with the ideal output signal. Based on the comparison result, the nonlinear influence factor is dynamically adjusted to correct the output signal of the MEMS gyroscope. The concepts involved here include:

[0109] Adaptive filtering technology: A filter technology that can automatically adjust its parameters according to changes in the input signal. The adaptive filter can monitor the output signal changes of the MEMS gyroscope in real time and continuously adjust its parameters according to the changes to achieve the best filtering effect.

[0110] Real-time monitoring: This means that the output signal changes of the MEMS gyroscope are continuously monitored throughout the entire working process so that any deviation from the ideal state can be discovered and handled in a timely manner.

[0111] Ideal output signal: Under ideal conditions, the standard signal value that the MEMS gyroscope should output, usually obtained through theoretical models or experimental calibration.

[0112] Compare: Compare the actual output signal with the ideal output signal to find the difference between the two.

[0113] Dynamically adjust the nonlinear influence factor: According to the difference between the actual output signal and the ideal output signal, the parameters of the nonlinear influence factor are adjusted in real time to reduce the drift error caused by temperature changes.

[0114] In the embodiment of the present application, adaptive filtering technology is used to monitor the output signal change of the MEMS gyroscope in real time, and the output signal change is compared with the ideal output signal, and the nonlinear influence factor is dynamically adjusted based on the comparison result to correct the output signal of the MEMS gyroscope. The specific embodiments are as follows:

[0115] Assume that in an experiment, the original output signal of the MEMS gyroscope is , the ideal output signal is , the nonlinear impact factor is , the parameters of the adaptive filter are ,in Indicates the current sampling point.

[0116] The goal of the adaptive filter is to minimize the error signal , the error signal is defined as:

[0117] ;

[0118] In order to monitor the output signal changes of the MEMS gyroscope in real time, we use an adaptive filter Perform filtering. The output of the filter is:

[0119] ;

[0120] in is the input vector, is the weight vector of the filter.

[0121] Error signal for:

[0122] ;

[0123] The adaptive filter is based on the error signal Update its weight Commonly used adaptive algorithms include the Least Mean Squares (LMS) algorithm or the Recursive Least Squares (RLS) algorithm.

[0124] Assuming the LMS algorithm is used, its update rule is:

[0125] ;

[0126] in is the step size factor, which controls the speed and stability of weight update. Specific embodiment:

[0128] Assume that the current moment , the output signal of the MEMS gyroscope is , the ideal output signal is , nonlinear impact factor , the initial weight of the adaptive filter is , step factor , the input vector ,in is the current temperature value, is the current time.

[0129] Assume that the current temperature is , the current time is seconds, the input vector is .

[0130] Error signal for:

[0131] ;

[0132] At this time, the error signal is zero, indicating that the output signal is consistent with the ideal signal, and there is no need to adjust the nonlinear influence factor. However, in order to demonstrate the dynamic adjustment process, assume that at the next moment , the temperature rises slightly, and the output signal becomes , the ideal output signal is still .

[0133] Error signal for:

[0134] ;

[0135] Input Vector , update the weight vector:

[0136] ;

[0137] Updated weight vector This is used for the next step of nonlinear influence factor adjustment. In this way, the adaptive filtering technology can monitor the output signal changes of the MEMS gyroscope in real time, and dynamically adjust the nonlinear influence factor according to the error signal to correct the output signal of the MEMS gyroscope, thereby minimizing the drift error caused by temperature changes.

[0138] Optionally, the method further includes: measuring the dynamic response characteristics of the MEMS gyroscope at different temperatures to obtain measurement results; and adjusting the nonlinear impact factor according to the measurement results to correct the output signal of the MEMS gyroscope.

[0139] In this step, the dynamic response characteristics of the MEMS gyroscope at different temperatures are measured to obtain measurement results; the nonlinear impact factor is adjusted according to the measurement results to correct the output signal of the MEMS gyroscope. The concepts involved here include:

[0140] Dynamic response characteristics: This refers to the behavior of the output signal of the MEMS gyroscope changing over time at different temperatures. Dynamic response characteristics usually include indicators such as the response speed, stability and noise level of the gyroscope.

[0141] Measurement results: Output signal data of the MEMS gyroscope under different temperature conditions obtained through experiments or other means, used to analyze its dynamic response characteristics.

[0142] Nonlinear influence factor: This is a factor used to characterize the degree of influence of temperature, time and frequency changes on the output signal of the MEMS gyroscope. By adjusting the nonlinear influence factor, the correction effect of the output signal can be optimized.

[0143] In the embodiment of the present application, the dynamic response characteristics of the MEMS gyroscope at different temperatures are measured to obtain measurement results; and the nonlinear influence factor is adjusted according to the measurement results to correct the output signal of the MEMS gyroscope. Specific embodiments are as follows:

[0144] Measuring the dynamic response characteristics of MEMS gyroscopes at different temperatures

[0145] Suppose in a laboratory environment, we test the dynamic response of a MEMS gyroscope under different temperature conditions. The test setup is as follows:

[0146] Temperature range: gradually increase from room temperature (20°C) to high temperature (60°C) in 5°C increments.

[0147] Test time for each temperature point: 30 minutes.

[0148] Data collection frequency: The output signal value is collected once per second.

[0149] Example:

[0150] Temperature setting and data collection: At 20°C, start the MEMS gyroscope and record its output signal for 30 minutes. Then gradually increase the temperature to the next temperature point (25°C), record the output signal for another 30 minutes, and so on until 60°C.

[0151] Data analysis: At each temperature point, the output signal variation curve over time is recorded. Assuming that at a certain temperature point (for example, 35°C), the output signal variation curve over time shows a certain drift phenomenon. The specific data is as follows:

[0152] Initial output signal: 1000mV

[0153] Final output signal: 1005mV

[0154] Time span: 30 minutes

[0155] Nonlinear influence factor adjustment: Based on the above measurement results, we found that temperature has a significant effect on the output signal. In order to correct this drift, it is necessary to adjust the nonlinear influence factor .

[0156] Assume that the initial value of the nonlinear impact factor is , the constant determined experimentally is , , , , , , .

[0157] According to the measurement results, the adjustment formula of the nonlinear impact factor is:

[0158] ;

[0159] Assume that at 35°C, the output signal drifts from 1000mV to 1005mV. We need to adjust the nonlinear effect factor to correct this drift. Assume that at 35°C, The adjustment value is 0.005, which means that at this temperature, the nonlinear influence factor needs to be increased by 0.005 to compensate for the drift.

[0160] The updated nonlinear impact factor is:

[0161] ;

[0162] in is the initial nonlinear impact factor value. Assume =0.01, then the adjusted nonlinear impact factor is:

[0163] ;

[0164] In this way, the nonlinear influence factor can be adjusted according to the dynamic response characteristics of the MEMS gyroscope at different temperatures, thereby correcting the output signal and reducing the drift error caused by temperature changes.

[0165] Optionally, the method further includes: adjusting the temperature gradient in the nonlinear influencing factor according to monitoring the ambient temperature change of the operating environment of the MEMS gyroscope to correct the output signal of the MEMS gyroscope.

[0166] In this step, the temperature gradient in the nonlinear influencing factor is adjusted according to the change of the ambient temperature of the operating environment of the MEMS gyroscope to correct the output signal of the MEMS gyroscope. The concepts involved here include:

[0167] Ambient temperature change: refers to the change in temperature over time in the environment where the MEMS gyroscope is located. Temperature changes may affect the output signal of the gyroscope.

[0168] Temperature gradient: It indicates the rate of change of temperature with spatial position, and is usually used to describe the spatial distribution of temperature field. Here, temperature gradient can be understood as the rate of change of temperature with time, that is, .

[0169] Nonlinear influence factor: It is a factor that comprehensively considers the influence of temperature, time, frequency and other factors on the output signal. By adjusting the temperature gradient term in the nonlinear influence factor, the output signal can be better corrected to reduce the drift error caused by temperature changes.

[0170] In the embodiment of the present application, according to the change of the ambient temperature of the operating environment of the MEMS gyroscope, the temperature gradient in the nonlinear influencing factor is adjusted to correct the output signal of the MEMS gyroscope. The specific embodiments are as follows:

[0171] Example:

[0172] Assume that in an experiment, the MEMS gyroscope experiences temperature changes within a specific period of time. We need to adjust the temperature gradient term in the nonlinear influencing factor according to these changes to correct the output signal.

[0173] Ambient temperature monitoring: We use the built-in temperature sensor to collect ambient temperature data every 1 second. Assume that within a certain period of time, the ambient temperature rises from 25°C to 30°C, which takes a total of 5 minutes.

[0174] Temperature gradient calculation: Calculate the temperature gradient based on the above temperature changes Assuming that the temperature rises from 25°C to 30°C in 5 minutes, the temperature gradient is:

[0175] ;

[0176] Adjustment of nonlinear influence factor: According to the definition of nonlinear influence factor, the temperature gradient term needs to be adjusted. Assume that the initial expression of nonlinear influence factor is:

[0177] ;

[0178] in, A =0.01, B =0.001, C =0.005, D =0.0001, E =0.001, H =0.00001, I =0.000001, F 0=1000Hz.

[0179] According to the temperature gradient calculated above , substituted into the nonlinear impact factor formula, the adjusted nonlinear impact factor is:

[0180] ;

[0181] Simplifying further:

[0182] ;

[0183] Assumptions ,but:

[0184] ;

[0185] In this way, we can adjust the temperature gradient term in the nonlinear influencing factor in real time according to the change of ambient temperature, so as to better correct the output signal of the MEMS gyroscope and reduce the drift error caused by temperature change.

[0186] Figure 2 A schematic diagram of a device for correcting temperature drift of a MEMS gyroscope is provided in an embodiment of the present application. Figure 2 As shown, the device comprises:

[0187] A recording module 21 is used to record the temperature value of the MEMS gyroscope in each sampling period through a built-in temperature sensor;

[0188] A calculation module 22, configured to calculate a nonlinear influence factor according to the temperature value, the acquired time, and the operating frequency of the MEMS gyroscope, wherein the nonlinear influence factor is used to balance the influence of the temperature value, the time, and the operating frequency on the output signal of the MEMS gyroscope;

[0189] The correction module 23 is used to correct the output signal of the MEMS gyroscope according to the nonlinear influencing factor using a multivariable dynamic compensation algorithm to minimize the drift error caused by temperature change.

[0190] Figure 2 The device for correcting the temperature drift of a MEMS gyroscope can be performed Figure 1 The implementation principle and technical effect of the method for correcting the temperature drift of a MEMS gyroscope described in the embodiment shown are not described in detail. The specific manner in which each module and unit performs operations in the device for correcting the temperature drift of a MEMS gyroscope in the above embodiment has been described in detail in the embodiment of the method, and will not be described in detail here.

[0191] In one possible design, Figure 2 The device for correcting the temperature drift of a MEMS gyroscope in the embodiment shown can be implemented as a computing device, such as Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32;

[0192] The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32 .

[0193] The processing component 32 is used to: record the temperature value of the MEMS gyroscope in each sampling period through a built-in temperature sensor; calculate a nonlinear influence factor based on the temperature value, the acquisition time and the operating frequency of the MEMS gyroscope, and the nonlinear influence factor is used to balance the influence of the temperature value, the time and the operating frequency on the output signal of the MEMS gyroscope; use a multivariable dynamic compensation algorithm to correct the output signal of the MEMS gyroscope according to the nonlinear influence factor to minimize the drift error caused by temperature changes.

[0194] The processing component 32 may include one or more processors to execute computer instructions to complete all or part of the steps in the above method. Of course, the processing component may also be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components to perform the above method.

[0195] The storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0196] Of course, the computing device may also include other components, such as input / output interfaces, display components, communication components, etc.

[0197] The input / output interface provides an interface between the processing component and the peripheral interface module, which may be an output device, an input device, etc.

[0198] The communication component is configured to facilitate, among other things, wired or wireless communications between the computing device and other devices.

[0199] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform, etc. In this case, the computing device can refer to a cloud server, and the above-mentioned processing components, storage components, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0200] The present application also provides a computer storage medium storing a computer program, wherein the computer program can achieve the above-mentioned Figure 1 A method for correcting temperature drift of a MEMS gyroscope according to the illustrated embodiment.

[0201] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0202] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0203] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0204] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for correcting temperature drift of a MEMS gyroscope, characterized in that: include: The temperature value of the MEMS gyroscope in each sampling period is recorded through the built-in temperature sensor; Calculating a nonlinear impact factor according to the temperature value, the acquired time, and the operating frequency of the MEMS gyroscope, wherein the nonlinear impact factor is used to balance the influence of the temperature value, the time, and the operating frequency on the output signal of the MEMS gyroscope; Using a multivariable dynamic compensation algorithm, the output signal of the MEMS gyroscope is corrected according to the nonlinear influencing factors to minimize the drift error caused by temperature changes; Among them, the nonlinear impact factor It is defined by the following formula: ； in, is the temperature value, For time, is the operating frequency, is the reference frequency, are constants determined experimentally, represents the temperature gradient, is the time-dependent phase shift function, the integral term Represents the cumulative effect of the temperature gradient from the initial moment to the current moment; Wherein, the step of correcting the output signal of the MEMS gyroscope according to the nonlinear influence factor comprises: The output signal of the MEMS gyroscope is corrected according to the nonlinear influence factor by the following formula: ； in, is the corrected output signal, is the original output signal, that is, the uncorrected MEMS gyroscope output signal, is the nonlinear influencing factor, For the ideal output signal, and is a predetermined amplitude and initial phase angle, is the angular frequency, which is related to the frequency of oscillation, is the coefficient related to the frequency change rate, is the frequency change rate, and is an additional modulation parameter related to time.

2. The method according to claim 1, characterized in that Also includes: Using adaptive filtering technology to monitor the output signal changes of the MEMS gyroscope in real time; The change of the output signal is compared with the ideal output signal, and based on the comparison result, the nonlinear impact factor is dynamically adjusted to correct the output signal of the MEMS gyroscope.

3. The method according to claim 1, characterized in that Also includes: Measuring the dynamic response characteristics of the MEMS gyroscope at different temperatures to obtain measurement results; The nonlinear impact factor is adjusted according to the measurement result to correct the output signal of the MEMS gyroscope.

4. The method according to claim 1, characterized in that: Also includes: According to monitoring the ambient temperature change of the operating environment of the MEMS gyroscope, the temperature gradient in the nonlinear influencing factor is adjusted to correct the output signal of the MEMS gyroscope.

5. The method according to claim 1, characterized in that The frequency change rate The calculation formula is as follows: ； in, is a constant determined experimentally, is the rate of change of the operating frequency over time, indicating the change of the operating frequency per unit time. is the rate of change of temperature over time, indicating the rate of temperature change, Indicates the operating frequency With reference frequency The ratio between is the time-dependent phase shift function.

6. A device for correcting temperature drift of a MEMS gyroscope, characterized in that: include: A recording module is used to record the temperature value of the MEMS gyroscope in each sampling period through a built-in temperature sensor; A calculation module, used to calculate a nonlinear influence factor according to the temperature value, the acquired time and the operating frequency of the MEMS gyroscope, wherein the nonlinear influence factor is used to balance the influence of the temperature value, the time and the operating frequency on the output signal of the MEMS gyroscope; A correction module, used for correcting the output signal of the MEMS gyroscope according to the nonlinear influencing factor using a multivariable dynamic compensation algorithm to minimize the drift error caused by temperature change; Among them, the nonlinear impact factor It is defined by the following formula: ； in, is the temperature value, For time, is the operating frequency, is the reference frequency, are constants determined experimentally, represents the temperature gradient, is the time-dependent phase shift function, the integral term Represents the cumulative effect of the temperature gradient from the initial moment to the current moment; Wherein, the step of correcting the output signal of the MEMS gyroscope according to the nonlinear influence factor comprises: The output signal of the MEMS gyroscope is corrected according to the nonlinear influence factor by the following formula: ； in, is the corrected output signal, is the original output signal, that is, the uncorrected MEMS gyroscope output signal, is the nonlinear influencing factor, For the ideal output signal, and is a predetermined amplitude and initial phase angle, is the angular frequency, which is related to the frequency of oscillation, is the coefficient related to the frequency change rate, is the frequency change rate, and is an additional modulation parameter related to time.

7. A computing device, characterized in that It comprises a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a method for correcting temperature drift of a MEMS gyroscope as described in any one of claims 1 to 5.

8. A computer storage medium, characterized in that A computer program is stored, and when the computer program is executed by a computer, a method for correcting temperature drift of a MEMS gyroscope as claimed in any one of claims 1 to 5 is implemented.

Images