Inertial measurement device and method with improved temperature drift and noise performance

Abstract

The present invention provides an inertial measurement device and an inertial measurement method. The inertial measurement device includes: multiple inertial sensors, each of which senses an inertial sensor signal; a filtering module for separating the inertial sensor signal of at least one of the multiple inertial sensors into a low-frequency component and a high-frequency component; a temperature calibration module for temperature-calibrating the low-frequency component of the inertial sensor signal of at least one of the multiple inertial sensors; a noise reduction module for noise-reducing the high-frequency component of the inertial sensor signal of at least one of the multiple inertial sensors; and a recombination module for recombinating the temperature-calibrated low-frequency component and the noise-reduced high-frequency component to form a recombined inertial sensor signal. This improves both the temperature drift performance and the noise performance of the inertial sensor signal.

Description

Technical Field

[0001] The present invention relates to the field of inertial measurement, and in particular to an inertial measurement device and an inertial measurement method with improved temperature drift and noise performance. Background Art

[0002] An inertial measurement unit (IMU) is an electronic device that uses a combination of accelerometers and gyroscopes to measure the acceleration and angular rate of a supporting substrate, and sometimes also includes a magnetometer to measure the magnetic field surrounding the supporting substrate.

[0003] like Figure 1 As shown, the inertial measurement unit detects linear acceleration by using one or more accelerometers and detects rotation rate by using one or more gyroscopes. Some inertial measurement units also include a magnetometer, which is typically used as a heading reference. For each of the three axes (i.e., pitch, roll, and yaw, X, Y, Z), an accelerometer and a gyroscope are configured. In one embodiment, the inertial measurement unit includes at least one 3-axis accelerometer and at least one 3-axis gyroscope. Optionally, the inertial measurement unit may also include at least one 3-axis magnetometer. In addition, the inertial measurement unit may also be connected to GPS and / or other sensors. The inertial measurement unit can estimate position and direction directly or indirectly. In another embodiment, the inertial measurement unit can communicate with the vehicle to control the steering, stability, or balance of the vehicle.

[0004] like Figure 2 As shown, the inertial measurement unit (IMU) can estimate its direction and position based on the angular velocity signal and acceleration signal it receives. The inertial measurement unit (IMU) estimates or updates its direction by accumulating or integrating the angular velocity signal. The inertial measurement unit (IMU) can estimate or update its position based on the direction estimate and acceleration signal it obtains. There are at least four stages in the process of estimating the position. The inertial measurement unit (IMU) first projects the acceleration signal onto the global axis using the direction estimate and acceleration signal it obtains. After that, the inertial measurement unit (IMU) corrects the projected acceleration signal based on gravity and generates a global acceleration signal. Based on the generated global acceleration signal and the initial velocity it obtains, the inertial measurement unit (IMU) can estimate its velocity. Based on its estimated velocity and the initial position it obtains, the inertial measurement unit (IMU) can estimate and update its position.

[0005] The bias drift and noise of the inertial measurement unit (IMU) will affect the positioning accuracy of the IMU. In current MEMS (Micro-Electro-Mechanical System)-based IMUs, bias drift is mainly determined by temperature error (also known as temperature drift), while noise is generally a function of device structure and manufacturing tolerances. The existing technology usually reduces noise through averaging, but there is no solution to reduce noise and temperature drift simultaneously. Summary of the Invention

[0006] An object of the present invention is to provide an inertial measurement device and an inertial measurement method, which can simultaneously reduce noise and temperature drift of inertial sensor signals.

[0007] To achieve the objectives of the invention, according to one aspect, the invention provides an inertial measurement device, comprising: a plurality of inertial sensors, each of which senses an inertial sensor signal; a filtering module for separating the inertial sensor signal of at least one of the plurality of inertial sensors into a low-frequency component and a high-frequency component; a temperature calibration module for performing temperature calibration on the low-frequency component of the inertial sensor signal of at least one of the plurality of inertial sensors; a noise reduction module for performing noise reduction processing on the high-frequency component of the inertial sensor signal of at least one of the plurality of inertial sensors; and a recombination module for recombinating the temperature-calibrated low-frequency component and the noise-reduced high-frequency component to form a recombined inertial sensor signal.

[0008] According to another aspect of the present invention, there is provided an inertial measurement method, comprising: obtaining a plurality of inertial sensing signals using a plurality of inertial sensors; separating the inertial sensing signal of at least one of the plurality of inertial sensors into a low-frequency component and a high-frequency component; temperature calibrating the low-frequency component of the inertial sensing signal of the at least one inertial sensor of the plurality of inertial sensors; performing noise reduction processing on the high-frequency component of the inertial sensing signal of the at least one inertial sensor of the plurality of inertial sensors; and recombining the temperature-calibrated low-frequency component and the noise-reduced high-frequency component to form a recombined inertial sensing signal.

[0009] Compared with the prior art, the present invention separates the inertial sensing signals of multiple inertial sensors into low-frequency and high-frequency components. The low-frequency components are then temperature-calibrated to optimize their temperature drift, while the high-frequency components are subjected to noise reduction processing to optimize their noise performance. Finally, the temperature-calibrated low-frequency components and the noise-reduced high-frequency components are recombined to form a reconstructed inertial sensing signal. The reconstructed inertial sensing signal has improved temperature drift and noise performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 Schematic diagram of the principle of an inertial measurement unit in the prior art;

[0011] Figure 2 A schematic diagram of the principle of estimating direction and position of an inertial measurement unit in the prior art;

[0012] Figure 3 is a structural diagram of an inertial measurement device in one embodiment of the present invention;

[0013] Figure 4 Schematic diagram of the working principle of the inertial measurement device in the present invention;

[0014] Figure 5 Schematic diagram of the residual temperature error loop of four inertial sensors;

[0015] Figure 6 Schematic diagram of dividing the residual temperature error loop into multiple temperature windows at predetermined temperature intervals in the present invention;

[0016] Figure 7 FIG. 4 is a flow chart of an inertial measurement method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to further illustrate the technical means and effects adopted by the present invention to achieve the predetermined purpose of the invention, the specific implementation methods, structures, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0018] The present invention provides an inertial measurement device that separates inertial sensing signals from multiple inertial sensors into low-frequency and high-frequency components. The low-frequency components are then temperature-calibrated to optimize their temperature drift, while the high-frequency components are subjected to noise reduction processing to optimize their noise performance. Finally, the temperature-calibrated low-frequency components and the noise-reduced high-frequency components are recombined to form a reconstructed inertial sensing signal with improved temperature drift and noise performance.

[0019] Figure 3 FIG. 3 is a structural diagram of an inertial measurement device 300 in one embodiment of the present invention. Figure 3 As shown, the inertial measurement device 300 includes a plurality of inertial measurement units (IMUs) 310 , a processing unit 320 , and support circuits 330 .

[0020] Figure 3The example shows three inertial measurement units 310. In fact, 2, 3, 4 or more IMUs 310 can be set as needed. These inertial measurement units 310 can be called inertial measurement arrays. Each inertial measurement unit 310 can include a 3-axis accelerometer and a 3-axis gyroscope. Optionally, the inertial measurement unit 310 can also include at least one 3-axis magnetometer. In some embodiments, each inertial measurement unit 310 can also include one or more single-axis accelerometers and / or one or more gyroscopes as needed. The 3-axis accelerometer can measure acceleration signals of 3 axes, and the 3-axis gyroscope can measure angular velocity signals of 3 axes. The accelerometer, the gyroscope and the magnetometer can all be called inertial measurement devices or inertial sensors.

[0021] The processing unit 320 can be a microprocessor unit (MCU). The processing unit 320 is supported by a support circuit 330 and provides various interfaces, such as UART and SPI, wherein the SPI or UART interface provides open connections with various host platforms. The inertial measurement unit 310 is connected to the processing unit 320 alone or in combination, and provides the measured inertial sensor signals to the processing unit 320. The processing unit 320 coordinates and controls the inertial measurement unit IMU and bears most of the signal processing load. In one embodiment, the processing unit 320 includes several logic units, which can perform digital signal filtering, sensor data enhancement processing, etc.

[0022] The support circuit 330 provides a combination of power, frequency, storage, and clock functions for the processing unit 320. The support circuit 330 may have a 3.5V power input, which may be provided by an AC-DC adapter or a battery. In one embodiment, the support circuit 330 may also include an analog front end that filters and digitizes the inertial sensor signals output by the inertial measurement unit 310 for processing by the logic unit of the processing unit 320.

[0023] Figure 4 The inertial measurement unit 310 provides inertial sensing signals a1, a2, a n , n is the number of inertial sensors and may be equal to 2. The processing unit 320 may include a filtering module 321, a temperature calibration module 322, a noise reduction module 323, and a reassembly module 324. Of course, in another embodiment, the filtering module 321, the temperature calibration module 322, the noise reduction module 323, and the reassembly module 324 may be implemented not in the processing unit 320 but in another separate module. The processing unit 320 processes the subsequent reassembled inertial sensor signals.

[0024] The filtering module 321 can separate the inertial sensing signals of each inertial sensor into low-frequency components and high-frequency components. Specifically, the filtering module 321 includes a plurality of low-pass filters LPF and a plurality of high-pass filters PHF complementary to the plurality of low-pass filters LPF. Each low-pass filter LPF is used to separate the inertial sensing signals a1, a2 or a3 of an inertial sensor. n Perform low-pass filtering to obtain the low-frequency component a of the inertial sensor signal of the inertial sensor 1L , a 2L or a nL Each high-pass filter HPF is used to filter the inertial sensor signal a1, a2 or a n Perform high-pass filtering to obtain the high-frequency component a of the inertial sensor signal of the inertial sensor 1H , a 2H or a nH The low-pass filter and high-pass filter corresponding to the same inertial sensor signal are complementary. The design of the LPF and HPF filters can use traditional IIR or FIR implementations or other standard filter mechanisms. Care must be taken to ensure digital stability. The typical cutoff frequency (if 0.1Hz) must be the same for the LPF and HPF filters to ensure that no distortion of the scale factor or amplitude response is introduced.

[0025] The temperature calibration module 322 is used to perform temperature calibration on the low frequency component of the inertial sensing signal of each inertial sensor. Specifically, the temperature calibration module 322 includes a plurality of temperature calibration units 3221. Each temperature calibration unit 3221 is used to calibrate the low frequency component a of the inertial sensing signal of an inertial sensor. 1L , a 2L or a nL and the corresponding temperature calibration coefficients C1(T), C2(T) or C n (T) is multiplied to obtain the low-frequency component after temperature correction.

[0026] It is important to know that even in the absence of rotation or acceleration, the gyroscopes and accelerometers inside the inertial measurement unit will show a certain measurement output, which is called bias drift. When the IMU is tested over a temperature range, this bias drift will vary with temperature. In addition, there will be some "lag" in the output of the inertial sensor. This "lag" is a function of temperature, which means that the output error of the inertial sensor at the same temperature is not a consistent value, but a function of the "temperature history" of the device. In this way, each inertial sensor can form a residual temperature error loop.

[0027] The width of this loop limits the calibration accuracy achievable using common temperature compensation techniques (such as polynomial or piecewise linear fit.) Additionally, the width of this loop varies widely between IMUs, and some IMUs will have a wider loop at certain temperatures than other devices. Figure 5 Schematic showing the residual temperature error loop for four sensors (rate gyros or accelerometers).

[0028] To minimize the uncertainty caused by hysteresis at any given temperature, the sensors are optimally combined by weighting the "best" sensor more heavily at any given temperature. The "best" sensor is determined by viewing the hysteresis loop as a probability error function, using the width of the loop as a measure of the standard deviation at any given temperature. Algorithms such as constrained least squares fitting can be used to determine the optimal weighting coefficients for the n sensors.

[0029] In a preferred embodiment, the temperature calibration coefficients C1(T), C2(T) or C n (T) is obtained by the following operations:

[0030] Measure the inertial sensor signals a1, a2 or a of each inertial sensor n The temperature response of each inertial sensor is calculated and temperature compensation is performed using piecewise linear or polynomial fitting;

[0031] The residual temperature error loop of each inertial sensor is measured and divided into multiple temperature windows at predetermined temperature intervals, such as Figure 6 As shown, for example, the temperature interval may be 1 degree;

[0032] A constrained least square fit is used to minimize the total error for each given temperature window, where the sum of the temperature calibration coefficients is 1, i.e. C1(T)+C s (T)+....C n (T) = 1.0;

[0033] A set of temperature calibration coefficients for each inertial sensor is obtained so that the total error in each given temperature window is minimized.

[0034] The obtained set of temperature calibration coefficients of each inertial sensor is stored in a memory, and in a subsequent temperature calibration process, the stored temperature calibration coefficients can be used to perform temperature calibration.

[0035] Of course, it is also possible to set a set of temperature calibration coefficients for each given temperature window of each inertial sensor, that is, to set multiple sets of temperature calibration coefficients, the temperature calibration coefficients of each inertial sensor are C1(T), C2(T) or C n (T) is obtained by the following operations:

[0036] Measure the inertial sensor signals a1, a2 or a of each inertial sensor n The temperature response of each inertial sensor is calculated and temperature compensation is performed using piecewise linear or polynomial fitting;

[0037] measuring a residual temperature error loop of each inertial sensor, and dividing the residual temperature error loop into a plurality of temperature windows at predetermined temperature intervals;

[0038] A set of temperature calibration coefficients for each given temperature window is obtained using constrained least squares fitting to minimize the total error for each given temperature window, where the sum of the individual temperature calibration coefficients is 1, i.e., C1(T)+C s (T)+....C n (T) = 1.0.

[0039] The noise reduction module 323 is used to perform noise reduction processing on the high frequency components of the inertial sensing signals in each inertial sensor. Specifically, the noise reduction module 323 includes a plurality of noise reduction units 3231. Each noise reduction unit is used to reduce the high frequency components a of the inertial sensing signals of an inertial sensor. 1H , a 2H or a nH With the corresponding noise reduction coefficient N1, N2 or N n Multiply to get the high-frequency component after noise reduction.

[0040] The noise reduction coefficient N1, N2 or N of each inertial sensor n Obtained by the following operations:

[0041] Measuring the noise of the inertial sensing signal of each inertial sensor;

[0042] The noise reduction coefficient of each inertial sensor is calculated according to the following formula to minimize the total noise and optimize the total RMS noise:

[0043] N Total 2 =N1*N a1 2 +N2*N a2 2 +...+N n *N an 2 , where N Total is the total noise, N a1, N anis the noise reduction coefficient of each inertial sensor signal a1, an.

[0044] The recombining module 324 is configured to recombine the temperature-calibrated low-frequency component and the noise-reduced high-frequency component to form a recombined inertial sensor signal. Preferably, the temperature-calibrated low-frequency component and the noise-reduced high-frequency component are added together to form a recombined inertial sensor signal. This recombined inertial sensor signal exhibits significantly improved temperature drift and noise performance.

[0045] This solution in the present invention can achieve at least a 10-fold improvement in temperature drift performance, while significantly improving noise performance, with the magnitude of the improvement being related to the square root of the number of inertial sensors.

[0046] In one embodiment, filtering, temperature calibration, noise reduction, and reassembly are performed independently on each type of multiple inertial sensors to improve the drift and noise characteristics of the inertial sensing signals of each type of inertial sensor. If the inertial sensor is a 3-axis accelerometer or a 3-axis gyroscope, filtering, temperature calibration, noise reduction, and reassembly are performed independently on each axis of the 3-axis accelerometer and / or 3-axis gyroscope.

[0047] The above descriptions all take an inertial measurement device as an example. Obviously, the present invention can also be implemented as an inertial measurement method. Figure 7 FIG. 7 is a flow chart of an inertial measurement method 700 in one embodiment of the present invention. Figure 7 As shown, the inertial measurement method 700 includes the following steps:

[0048] Step 710, obtaining a plurality of inertial sensing signals using a plurality of inertial sensors;

[0049] Step 720 , separating an inertial sensing signal of at least one inertial sensor among the plurality of inertial sensors into a low-frequency component and a high-frequency component;

[0050] Step 730 , performing temperature calibration on a low-frequency component of an inertial sensing signal of at least one inertial sensor among the plurality of inertial sensors;

[0051] Step 740 , performing noise reduction processing on a high-frequency component of an inertial sensing signal of at least one inertial sensor among the plurality of inertial sensors;

[0052] Preferably, at least one inertial sensor among the plurality of inertial sensors is a plurality of or all of the inertial sensors among the plurality of inertial sensors.

[0053] Step 750 : Recombining the temperature-calibrated low-frequency component and the noise-reduced high-frequency component to form a recombined inertial sensing signal.

[0054] In one embodiment, the low-frequency component of the inertial sensor signal of each inertial sensor is multiplied by the corresponding temperature calibration coefficient to obtain the temperature-calibrated low-frequency component. Preferably, the temperature calibration coefficient of each inertial sensor is obtained by the following operation:

[0055] Measure the inertial sensor signals a1, a2 or a of each inertial sensor n The temperature response of each inertial sensor is calculated and temperature compensation is performed using piecewise linear or polynomial fitting;

[0056] The residual temperature error loop of each inertial sensor is measured and divided into multiple temperature windows at predetermined temperature intervals, such as Figure 5 As shown, for example, the temperature interval may be 1 degree;

[0057] A constrained least square fit is used to minimize the total error for each given temperature window, where the sum of the temperature calibration coefficients is 1, i.e. C1(T)+C s (T)+....C n (T) = 1.0;

[0058] A set of temperature calibration coefficients for each inertial sensor is obtained so that the total error in each given temperature window is minimized.

[0059] Of course, it is also possible to set a set of temperature calibration coefficients for each given temperature window of each inertial sensor, that is, to set multiple sets of temperature calibration coefficients, the temperature calibration coefficients of each inertial sensor are C1(T), C2(T) or C n (T) is obtained by the following operations:

[0060] Measure the inertial sensor signals a1, a2 or a of each inertial sensor n The temperature response of each inertial sensor is calculated and temperature compensation is performed using piecewise linear or polynomial fitting;

[0061] measuring a residual temperature error loop of each inertial sensor, and dividing the residual temperature error loop into a plurality of temperature windows at predetermined temperature intervals;

[0062] A set of temperature calibration coefficients for each given temperature window is obtained using constrained least squares fitting to minimize the total error for each given temperature window, where the sum of the individual temperature calibration coefficients is 1, i.e., C1(T)+C s (T)+....C n (T) = 1.0.

[0063] In one embodiment, the high-frequency component of the inertial sensor signal of each inertial sensor is multiplied by the corresponding noise reduction coefficient to obtain the noise-reduced high-frequency component. Preferably, the noise reduction coefficient of each inertial sensor is obtained by the following operation:

[0064] Measuring the noise of the inertial sensing signal of each inertial sensor;

[0065] The noise reduction coefficient of each inertial sensor is calculated according to the following formula to minimize the total noise and optimize the total RMS noise:

[0066] N Total 2 =N1*N a1 2 +N2*N a2 2 +...+N n *N an 2 ,

[0067] where N Total is the total noise, N a1, , N a2 , N an is the noise of each inertial sensor signal a1, a2, an, N1, N2, N n is the noise coefficient of each inertial sensor signal a1, a2, an.

[0068] As used herein, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion of elements other than the listed elements and may also include additional elements not specifically listed.

[0069] In this document, directional terms such as front, back, top, and bottom are defined based on the positions of components in the accompanying drawings and relative to each other, and are intended only for clarity and convenience in describing the technical solution. It should be understood that the use of these directional terms should not limit the scope of protection claimed in this application.

[0070] In the absence of conflict, the above embodiments and features in the embodiments may be combined with each other.

[0071] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. An inertial measurement device, characterized in that: It includes: A plurality of inertial sensors, wherein each inertial sensor senses an inertial sensing signal, and each inertial sensor is an accelerometer, a gyroscope, or a magnetometer; a filtering module, configured to separate an inertial sensing signal of one of the plurality of inertial sensors into a low-frequency component and a high-frequency component; a temperature calibration module, configured to perform temperature calibration on a low-frequency component of an inertial sensing signal of the one inertial sensor among the plurality of inertial sensors; a noise reduction module, configured to perform noise reduction processing on a high-frequency component of an inertial sensing signal of the one inertial sensor among the plurality of inertial sensors; The recombining module is used to recombine the low-frequency component after temperature calibration and the high-frequency component after noise reduction processing of the same inertial sensor to form a recombined inertial sensor signal.

2. The inertial measurement device according to claim 1, wherein The filtering module includes multiple low-pass filters and multiple high-pass filters complementary to the multiple low-pass filters. Each low-pass filter performs low-pass filtering on the inertial sensor signal of an inertial sensor to obtain a low-frequency component of the inertial sensor signal of the inertial sensor. Each high-pass filter performs high-pass filtering on the inertial sensor signal of an inertial sensor to obtain a high-frequency component of the inertial sensor signal of the inertial sensor.

3. The inertial measurement device according to claim 1, wherein The temperature calibration module includes a plurality of temperature calibration units, each of which is used to multiply a low-frequency component of an inertial sensor signal of an inertial sensor by a corresponding temperature calibration coefficient to obtain a temperature-calibrated low-frequency component.

4. The inertial measurement device according to claim 3, wherein The temperature calibration coefficients for each inertial sensor are obtained as follows: Measuring the temperature response of the inertial sensing signal of each inertial sensor and performing temperature compensation on each inertial sensor using piecewise linear or polynomial fitting; measuring a residual temperature error loop of each inertial sensor, and dividing the residual temperature error loop into a plurality of temperature windows at predetermined temperature intervals; A constrained least squares fit is used to minimize the total error for each given temperature window, where the sum of the individual temperature calibration coefficients is 1. Determine a set of temperature calibration coefficients for each inertial sensor so that the total error in each given temperature window is minimized; or The temperature calibration coefficients for each inertial sensor are obtained as follows: Measuring the temperature response of the inertial sensing signal of each inertial sensor and performing temperature compensation on each inertial sensor using piecewise linear or polynomial fitting; measuring a residual temperature error loop of each inertial sensor, and dividing the residual temperature error loop into a plurality of temperature windows at predetermined temperature intervals; A set of temperature calibration coefficients for each given temperature window is obtained using constrained least squares fitting to minimize the total error for each given temperature window, where the sum of the individual temperature calibration coefficients is 1.

5. The inertial measurement device according to claim 1, wherein The noise reduction module includes a plurality of noise reduction units, each of which is used to multiply a high-frequency component of an inertial sensor signal of an inertial sensor by a corresponding noise reduction coefficient to obtain a noise-reduced high-frequency component.

6. The inertial measurement device according to claim 5, wherein The noise reduction coefficient of each inertial sensor is obtained by the following operation: Measuring the noise of the inertial sensing signal of each inertial sensor; The noise reduction coefficient of each inertial sensor is calculated according to the following formula to minimize the total noise: N Total 2 =N1*N a1 2 +N2*N a2 2 +...+N n *N an 2 , where N Total is the total noise, N a1, , N a2 , N an is the noise of each inertial sensor signal a1, a2, an, N1, N2, N n is the noise coefficient of each inertial sensor signal a1, a2, an.

7. The inertial measurement device according to any one of claims 1 to 6, wherein: There are multiple types of inertial sensors, and there are multiple inertial sensors of each type. Each type of multiple inertial sensors is independently subjected to filtering, temperature calibration, noise reduction, and reorganization processing.

8. The inertial measurement device according to claim 7, wherein One type of inertial sensor is an accelerometer, and another type of inertial sensor is a gyroscope.

9. The inertial measurement device according to claim 8, wherein An accelerometer and a gyroscope form a group to form an inertial measurement unit, and multiple accelerometers and multiple gyroscopes form multiple inertial measurement units. These multiple inertial measurement units are called an inertial measurement array.

10. The inertial measurement device according to claim 8, wherein The acceleration sensor is a 3-axis acceleration sensor, and the gyroscope is a 3-axis gyroscope. Each axis of the 3-axis acceleration sensor and / or the 3-axis gyroscope is independently subjected to filtering, temperature calibration, noise reduction, and reorganization processing.

11. An inertial measurement method, characterized in that: It includes: A plurality of inertial sensors are used to obtain a plurality of inertial sensing signals, each of the inertial sensors being an accelerometer, a gyroscope or a magnetometer; separating an inertial sensing signal of one of the plurality of inertial sensors into a low-frequency component and a high-frequency component; performing temperature calibration on a low-frequency component of an inertial sensing signal of an inertial sensor among the plurality of inertial sensors; performing noise reduction processing on a high-frequency component of an inertial sensing signal of an inertial sensor among the plurality of inertial sensors; The low-frequency component after temperature calibration and the high-frequency component after noise reduction of the same inertial sensor are recombined to form a reconstructed inertial sensing signal.

12. The inertial measurement method according to claim 11, wherein: A low-pass filter among a plurality of low-pass filters is used to perform low-pass filtering on an inertial sensor signal of an inertial sensor to obtain a low-frequency component of the inertial sensor signal of the inertial sensor, and a high-pass filter among a plurality of high-pass filters is used to perform high-pass filtering on an inertial sensor signal of an inertial sensor to obtain a high-frequency component of the inertial sensor signal of the inertial sensor.

13. The inertial measurement method according to claim 11, wherein: The low-frequency component of the inertial sensing signal of each inertial sensor is multiplied by the corresponding temperature calibration coefficient to obtain the low-frequency component after temperature calibration.

14. The inertial measurement method according to claim 13, wherein: The temperature calibration coefficients for each inertial sensor are obtained as follows: Measuring the temperature response of the inertial sensing signal of each inertial sensor and performing temperature compensation on each inertial sensor using piecewise linear or polynomial fitting; measuring a residual temperature error loop of each inertial sensor, and dividing the residual temperature error loop into a plurality of temperature windows at predetermined temperature intervals; A constrained least squares fit is used to minimize the total error for each given temperature window, where the sum of the individual temperature calibration coefficients is 1. Determine a set of temperature calibration coefficients for each inertial sensor so that the total error in each given temperature window is minimized; or The temperature calibration coefficients for each inertial sensor are obtained as follows: Measuring the temperature response of the inertial sensing signal of each inertial sensor and performing temperature compensation on each inertial sensor using piecewise linear or polynomial fitting; measuring a residual temperature error loop of each inertial sensor, and dividing the residual temperature error loop into a plurality of temperature windows at predetermined temperature intervals; A set of temperature calibration coefficients for each given temperature window is obtained using constrained least squares fitting to minimize the total error for each given temperature window, where the sum of the individual temperature calibration coefficients is 1.

15. The inertial measurement method according to claim 11, wherein: The high-frequency component of the inertial sensing signal of each inertial sensor is multiplied by the corresponding noise reduction coefficient to obtain the high-frequency component after noise reduction.

16. The inertial measurement method according to claim 15, wherein: The noise reduction coefficient of each inertial sensor is obtained by the following operation: Measuring the noise of the inertial sensing signal of each inertial sensor; By minimizing the total noise N according to the following formula Total To obtain the noise reduction coefficient of each inertial sensor: N Total 2 =N1*N a1 2 +N2*N a2 2 +...+N n *N an 2 , where N Total is the total noise, N a1, , N a2 , N an is the noise of each inertial sensor signal a1, a2, an, N1, N2, N n is the noise coefficient of each inertial sensor signal a1, a2, an.

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