A method for temperature modeling and compensation of a fiber-optic gyroscope based on double temperature sensors

Abstract

The application discloses a kind of temperature modeling and compensation method of fiber-optic gyroscope based on double temperature sensor, including temperature data acquisition using temperature sensor fixed in the inside and outside of fiber coil base, calculate the time gradient and spatial gradient of fiber coil temperature, as the input information of fiber-optic gyroscope temperature model.Then, set acquisition parameters in high-low temperature box, record fiber-optic gyroscope output, temperature and temperature rate of change curve.According to data characteristics, segment data, and use each section of data to carry out multiple linear regression fitting, establish fiber-optic gyroscope temperature model.Then, calculate the gyroscope calibration factor at each temperature, and carry out polynomial fitting to reduce nonlinearity.Finally, pre-process the collected temperature data, substitute into temperature model to calculate real-time zero bias temperature compensation amount, complete online temperature compensation.Effectively improve the performance stability and measurement accuracy of fiber-optic gyroscope in different temperature environments.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of fiber-optic gyroscope, and particularly relates to a fiber-optic gyroscope temperature modeling and compensation method based on double temperature sensors. BACKGROUND

[0002] As a high-precision and high-stability angular velocity sensor, the fiber-optic gyroscope has a wide application prospect in many fields such as aerospace, navigation and positioning, and inertial guidance. However, the performance of the fiber-optic gyroscope is restricted by various environmental factors, especially the temperature factor has a significant impact on its performance. The change of temperature not only causes the physical properties of the optical elements, mechanical structures and electronic devices in the fiber-optic gyroscope to change, but also causes the fluctuations of the optical path length, refractive index and other parameters in the fiber-optic gyroscope, thereby affecting its measurement accuracy and stability. Therefore, the temperature problem has become a key problem restricting the fiber-optic gyroscope to move towards the road of engineering practicality.

[0003] In order to solve the temperature problem of the fiber-optic gyroscope, researchers have proposed various methods. Among them, reasonably designing and improving the structure of the gyroscope is a basic method, which reduces the direct influence of temperature on the performance of the gyroscope by optimizing the external shape and internal structure of the gyroscope. Another method is to add temperature control equipment such as heating elements or refrigeration systems inside the gyroscope, which actively controls the working temperature of the gyroscope to keep it within a relatively stable range. In addition, the software method for temperature modeling and compensation is also a very effective means, which establishes a mathematical model between the performance of the fiber-optic gyroscope and the temperature, and corrects the output signal of the gyroscope in real time, so as to eliminate the influence of temperature on the performance of the gyroscope.

[0004] The prior art has some deficiencies. Although there are currently various methods for solving the temperature problem of the fiber optic gyroscope, there are still some deficiencies. For example, although the method of reasonably designing and improving the structure of the gyroscope can reduce the influence of temperature on the performance of the gyroscope to a certain extent, it is often limited by factors such as the size, weight and cost of the gyroscope, and is difficult to be widely used in engineering. Although the method of adding a temperature control device can actively control the working temperature of the gyroscope, it will increase the complexity and energy consumption of the gyroscope, and the precision and stability of the temperature control system also directly affect the performance of the gyroscope. The temperature modeling and compensation technology in the software method has become the mainstream method for solving the temperature problem of the fiber optic gyroscope, but due to the complexity and nonlinearity of the fiber optic gyroscope, it is still a great challenge to establish an accurate temperature model. In addition, the updating and maintenance of the temperature model also require a large amount of experimental data and computing resources, which increases the difficulty and cost of engineering implementation. Therefore, how to further improve the temperature stability and measurement accuracy of the fiber optic gyroscope is still a technical problem to be solved. SUMMARY

[0005] The purpose of the present application is to overcome the deficiencies of the prior art and to achieve the above purpose. A fiber optic gyroscope temperature modeling and compensation method based on double temperature sensors is used to solve the problems raised in the background art.

[0006] A fiber optic gyroscope temperature modeling and compensation method based on double temperature sensors, comprising the following steps:

[0007] Step S1, based on the first temperature sensor and the second temperature sensor fixed on the inside and outside of the fiber coil base, collecting temperature data, subtracting the measurement value of the first temperature sensor at the current time from the measurement value at the previous preset time to obtain the time gradient T'(n) of the fiber coil temperature; and subtracting the measurement values of the first temperature sensor and the second temperature sensor at the same time to obtain the spatial gradient ΔT(n) of the fiber coil temperature as the input information of the fiber optic gyroscope temperature model;

[0008] Step S2, fixing the fiber optic gyroscope in a high-low temperature chamber, setting the collection parameters, starting the gyroscope under room temperature conditions, starting the temperature chamber after the temperature of the gyroscope is stable, setting the collection conditions and recording the data at the same time, finally obtaining sample data, and obtaining the fiber optic gyroscope output curve, temperature output curve and temperature change rate curve;

[0009] Step S3, according to the output data characteristics of the fiber optic gyroscope, the data obtained in step S2 are divided into nine segments;

[0010] Step S4, the segmented gyroscope full-temperature experiment data are used for parameter fitting of multivariate linear regression respectively, the model parameters in the corresponding temperature environment are obtained, and the fiber optic gyroscope temperature model is established;

[0011] Step S5, presetting parameters, collecting gyro original output, calculating gyro calibration factor at each temperature, performing polynomial fitting on the calibration factor, and reducing the nonlinearity of the calibration factor;

[0012] Step S6, pre-processing the collected temperature data, obtaining the time gradient and space gradient of the temperature by subtraction, substituting them into the fiber optic gyroscope temperature model calculated in step S4 to calculate the real-time bias temperature compensation amount, and then performing temperature compensation reduction to complete the online temperature compensation.

[0013] As a further scheme of the present application: the first temperature sensor and the second temperature sensor in step S1 both adopt 18B20 temperature sensors, and are fixed at the inside and the outer wall of the symmetric position of the fiber coil base respectively, the first temperature sensor is installed inside the fiber coil, and the second temperature sensor is installed on the outer wall of the fiber coil.

[0014] As a further scheme of the present application: the specific steps of collecting temperature data in step S1 include:

[0015] The time gradient T'(n) of the fiber coil temperature and the space gradient ΔT(n) of the fiber coil temperature are as follows:

[0016] T'(n) = T1(n) - T1(n-1);

[0017] ΔT(n) = T1(n) - T2(n);

[0018] Wherein, T1(n) and T2(n) are the measurement values of the first temperature sensor and the second temperature sensor at n time respectively.

[0019] As a further scheme of the present application: the specific steps in step S2 include:

[0020] The fiber optic gyroscope is fixed in the high-low temperature box, the sampling frequency of the gyroscope is 100 Hz, the temperature sampling period is 1 s, and the temperature change rate is set to 1° / min;

[0021] The gyroscope is started under room temperature conditions, the temperature of the oven is reduced to-40℃ after the temperature of the gyroscope is stable, and the gyroscope works at this temperature for 90 minutes, then the temperature of the oven is increased to 60℃, and the gyroscope works at this temperature for 90 minutes, then the temperature of the oven is reduced to room temperature, and the test is ended after the output of the fiber optic gyroscope reaches stability again.

[0022] The output data of the fiber optic gyroscope is subjected to 100ms smoothing processing to obtain the output data of the fiber optic gyroscope, then the temperature change rate is calculated to obtain sample data, and the output curve of the fiber optic gyroscope, the temperature output curve, and the temperature change rate curve are obtained.

[0023] As a further scheme of the present application: the specific steps in the step S4 include:

[0024] In the model parameter fitting, the full-temperature test data of the fiber optic gyroscope is segmented according to different temperature conditions, and then the parameter fitting of the multivariate linear regression is carried out by using each segment of data respectively to obtain the model parameters in the corresponding temperature environment.

[0025] In the compensation, each related variable is calculated in real time, the data segment is determined, and then the corresponding model parameters are called to carry out the compensation calculation, and the temperature polynomial model is as follows:

[0026]

[0027] Wherein, L0 is a constant term, T is a relative temperature, dT / dt is a change rate, A i and B j are polynomial coefficients, epsilon is a random error, and i and j are the highest order.

[0028] As a further scheme of the present application: the specific steps in the step S5 include:

[0029] The fiber optic gyroscope is fixed in a high-low temperature box with a turntable, the sensitive axis of the gyroscope is parallel to the rotating shaft of the turntable, and the experimental temperature is set at 6 temperature points of-40 DEG C, -20 DEG C, 0 DEG C, +20 DEG C, +40 DEG C and +60 DEG C.

[0030] After the internal temperature of the gyroscope is stabilized at each set temperature, the turntable is rotated in turn, the angular velocity is ±2.5 ° / s, ±4 ° / s, ±6.4 ° / s, ±10 ° / s, ±15 ° / s, ±30 ° / s, ±45 ° / s and ±60 ° / s respectively, the original output of the gyroscope is collected, the calibration factor of the gyroscope at each temperature is calculated, and the calibration factor is fitted by a polynomial.

[0031] As a further scheme of the present application: the specific steps in the step S6 include:

[0032] Based on the single-chip microcomputer, the collected temperature data is preprocessed first, the time gradient and the space gradient of the temperature are obtained by subtraction, and then the temperature model of the fiber optic gyroscope calculated in the step S3 is substituted into the temperature model to calculate the real-time zero bias temperature compensation amount, the data is sent to the FPGA for temperature compensation reduction, so that the online temperature compensation is realized.

[0033] Compared with the prior art, the present application has the following technical effects:

[0034] By analyzing the influence of the temperature change rate on the output accuracy of the fiber optic gyroscope, the accurate temperature model and the calculation method are given, and the output error of the fiber optic gyroscope caused by the temperature change can be effectively reduced.

[0035] The general formula of the temperature model of the fiber optic gyroscope is given by induction and summary, and for different fiber optic gyroscopes, the output data of the fiber optic gyroscope can be obtained after the oven cycle test, and the general model can be modeled according to the output data, and the parameters are solved by the multiple linear regression method, so that the accurate temperature model is obtained, and the applicability is relatively strong.

[0036] The collected temperature data is preprocessed, substituted into the preset temperature model for calculation, and the real-time zero bias temperature compensation amount is obtained, and the data is sent to the FPGA for temperature compensation reduction, so that online temperature compensation can be realized, and the real-time performance is relatively good. BRIEF DESCRIPTION OF DRAWINGS

[0037] The specific embodiments of the application will be described in detail below with reference to the accompanying drawings:

[0038] Figure 1 The steps of the modeling and compensation method of the disclosed embodiment of the application are shown in the schematic diagram;

[0039] Figure 2 The installation schematic diagram of the sampling point of the temperature sensor of the disclosed embodiment of the application is shown in the schematic diagram;

[0040] Figure 3 The gyro output curve of the disclosed embodiment of the application is shown in the schematic diagram;

[0041] Figure 4 The temperature output curve of the disclosed embodiment of the application is shown in the schematic diagram;

[0042] Figure 5 The temperature change rate curve of the disclosed embodiment of the application is shown in the schematic diagram;

[0043] Figure 6 The full-temperature temperature curve of the disclosed embodiment of the application is shown in the schematic diagram;

[0044] Figure 7 The segmented fitting curve of the disclosed embodiment of the application is shown in the schematic diagram;

[0045] Figure 8 The temperature compensation effect diagram of the disclosed embodiment of the application is shown in the schematic diagram;

[0046] Figure 9 The gyro calibration factor and rotational speed curve relationship diagram of the disclosed embodiment of the application under different temperatures is shown in the schematic diagram;

[0047] Figure 10 The calibration factor and temperature curve of the disclosed embodiment of the application is shown in the schematic diagram. DETAILED DESCRIPTION

[0048] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of the present application.

[0049] Please refer to Figure 1 In the embodiments of the present application, a fiber-optic gyroscope temperature modeling and compensation method based on double temperature sensors comprises the following steps:

[0050] In step S1, temperature data is collected based on a first temperature sensor and a second temperature sensor fixed on both sides of a fiber coil base. The current measurement value of the first temperature sensor is subtracted from the measurement value at a previous preset time to obtain a time gradient T'(n) of the fiber coil temperature. The measurement value of the first temperature sensor at the same time is subtracted from the measurement value of the second temperature sensor to obtain a spatial gradient ΔT(n) of the fiber coil temperature, which is used as input information of a fiber-optic gyroscope temperature model.

[0051] In step S11, the temperature sensor is installed.

[0052] As shown in Figure 2 FIG. 1 is a schematic diagram of a sampling point of a temperature sensor. In step S1, two 18B20 temperature sensors are used as the first temperature sensor and the second temperature sensor, and are fixed on the inner wall and the outer wall of the fiber coil base at symmetrical positions. The first temperature sensor is installed inside the fiber coil, and the second temperature sensor is installed on the outer wall of the fiber coil.

[0053] In step S12, temperature data is collected.

[0054] In step S12, temperature data is collected.

[0055] The current measurement value of the first temperature sensor installed in step S11 is subtracted from the measurement value at a previous time (30-second interval) to obtain a time gradient T'(n) of the fiber coil temperature. The measurement value of the first temperature sensor at the same time is subtracted from the measurement value of the second temperature sensor to obtain a spatial gradient ΔT(n) of the fiber coil temperature, which is used as input information of a fiber-optic gyroscope temperature model.

[0056] T'(n) = T1(n) - T1(n-1);

[0057] ΔT(n) = T1(n) - T2(n);

[0058] Wherein, T1(n) and T2(n) are the measurement values of the first temperature sensor and the second temperature sensor at the n time, respectively.

[0059] Step S2, fix the fiber optic gyroscope in the high-low temperature box, set the acquisition parameters, start the gyroscope under room temperature conditions, start the temperature box after the gyroscope temperature stabilizes, set the acquisition condition and record the data at the same time, finally obtain the sample data, get the fiber optic gyroscope output curve, temperature output curve and temperature change rate curve, the specific steps include:

[0060] As shown in Figure 3 , the diagram is a gyroscope output curve diagram;

[0061] As shown in Figure 4 , the diagram is a temperature output curve diagram;

[0062] As shown in Figure 5 , the diagram is a temperature change rate curve diagram;

[0063] First, the fiber optic gyroscope is firmly fixed in the high-low temperature box, which is to ensure that the fiber optic gyroscope can remain stable during the experiment and is not disturbed by the external environment. In the experimental setup, the sampling frequency of the gyroscope is set to 100 Hz, which means that the gyroscope will perform 100 data samplings per second to obtain enough dense data points for subsequent analysis. At the same time, the temperature sampling period is set to 1 second, that is, the temperature change in the temperature box is recorded once every second to ensure that the details of the temperature change can be captured. The temperature change rate is set to 1 degree Celsius per minute, which is a relatively slow change rate, which helps to observe the performance change of the fiber optic gyroscope at different temperatures in more detail.

[0064] Next, start the fiber optic gyroscope under room temperature conditions and let it run for a period of time until the temperature stabilizes. This is to ensure that the gyroscope has adapted to the current ambient temperature before the experiment begins, thereby avoiding initial errors caused by temperature changes. After the temperature of the gyroscope stabilizes, start the high-low temperature box and begin the temperature cycle experiment. First, lower the temperature in the temperature box to -40 degrees Celsius and let the fiber optic gyroscope work at this temperature for 90 minutes. This low temperature environment helps to observe the performance of the gyroscope under extreme cold conditions. Then, gradually increase the temperature in the temperature box to 60 degrees Celsius and let the gyroscope work at this temperature for another 90 minutes. The high temperature environment is used to test the stability and reliability of the gyroscope under high temperature conditions. Finally, lower the temperature in the temperature box to room temperature and end the entire experiment after the output of the fiber optic gyroscope stabilizes again.

[0065] After the experiment is completed, the output data of the fiber-optic gyroscope needs to be processed and analyzed. First, the output data of the gyroscope is smoothed for 100 milliseconds to eliminate data fluctuations caused by noise or interference. The smoothed data will be used to draw the output curve of the fiber-optic gyroscope to visually show the performance changes of the gyroscope at different temperatures. At the same time, the temperature change rate needs to be calculated to obtain more detailed sample data. These sample data will be used to draw temperature output curves and temperature change rate curves to better understand the performance of the fiber-optic gyroscope under different temperature conditions.

[0066] Step S3, according to the characteristics of the fiber-optic gyroscope output data, the data obtained in step S2 is divided into nine segments, the specific steps include:

[0067] Segmentation of experimental data: the temperature effect error of the fiber-optic gyroscope shows different change rules under different temperature conditions (for example, temperature approximately stable and severe oscillation, temperature rise and fall, and variable temperature rate fast and slow). According to the characteristics of the fiber-optic gyroscope output data, the data obtained in step S2 is divided into nine segments. The specific segmentation method is shown in Table 1 below.

[0068] Table 1

[0069] Paragraph number Temperature profile T dT / dt d(dT / dt)dt 1 Temperature approximately constant Extremum constant (-r，r) (-∞，+∞) 2 Cooling and rate increasing [T < T0] (-∞,r] (-∞，0) 3 Cooling and rate decreasing [T < T0] (-∞,r] (0，+∞) 4 Heating and rate increasing [T < To] (r,+∞) (0，+∞) 5 Heating and rate decreasing [T < T0] (r,+∞) (-∞，0) 6 Heating and rate increasing [T > T0] (r,+∞) (0，+∞) 7 Heating and rate decreasing [T > T0] (r,+∞) (-∞，0) 8 Cooling and rate increasing [T > T0] (-∞，-r] (-∞，0) 9 Cooling and rate decreasing [T > T0] (-∞，-r] (0，+∞)

[0070] Step S4, establish the temperature model of the fiber-optic gyroscope:

[0071] As shown in Figure 6 , the graph is a full-temperature temperature curve;

[0072] After the segmented gyroscope full-temperature experimental data is segmented by the above step S3, the segmented data is used for multiple linear regression parameter fitting, the model parameters under the corresponding temperature environment are obtained, and the temperature model of the fiber-optic gyroscope is established. The specific steps include:

[0073] In the model parameter fitting, the full-temperature test data of the fiber-optic gyroscope is segmented according to different temperature conditions, and then the segmented data is used for multiple linear regression parameter fitting to obtain the model parameters under the corresponding temperature environment.

[0074] As shown in Figure 7 , the graph is a segmented fitting curve;

[0075] In the compensation, the relevant variables are calculated in real time, the data segment is determined, and the corresponding model parameters are called for compensation calculation. The temperature polynomial model is as follows:

[0076]

[0077] Where L0 is a constant term, T is the relative temperature, dT / dt is the change rate, Ai and B j ε represents the polynomial coefficients, ε represents the random error, and i and j represent the highest order.

[0078] Step S5, Fiber optic gyroscope calibration factor temperature error compensation:

[0079] In this embodiment, as Figure 8 As shown in the figure, the temperature compensation effect diagram is displayed.

[0080] Preset parameters, collect the raw output of the gyroscope, calculate the gyroscope calibration factor at each temperature, and perform polynomial fitting on the calibration factor to reduce its nonlinearity. Specific steps include:

[0081] like Figure 9 As shown in the figure, the graph illustrates the relationship between the gyroscope calibration factor and rotational speed at different temperatures.

[0082] The fiber optic gyroscope was fixed in a high and low temperature chamber with a turntable. The sensitive axis of the gyroscope was parallel to the rotation axis of the turntable. Six temperature points were set at -40℃, -20℃, -0℃, +20℃, +40℃, and +60℃.

[0083] like Figure 10 As shown in the figure, the graph represents the relationship between the calibration factor and temperature.

[0084] After the internal temperature of the gyroscope stabilizes at each set temperature, the turntable is rotated sequentially at angular velocities of ±2.5° / s, ±4° / s, ±6.4° / s, ±10° / s, ±15° / s, ±30° / s, ±45° / s, and ±60° / s, respectively. The raw output of the gyroscope is collected, the gyroscope calibration factor at each temperature is calculated, and polynomial fitting is performed on the calibration factor.

[0085] Step S6, Online Temperature Compensation:

[0086] In the signal processing board of the fiber optic gyroscope, the microcontroller C8051 is responsible for both temperature data acquisition and online temperature compensation calculation. It preprocesses the acquired temperature data, obtains the time gradient and spatial gradient of the temperature by subtraction, and substitutes them into the fiber optic gyroscope temperature model calculated in step S4 to obtain the real-time zero-bias temperature compensation amount. Then, it performs temperature compensation reduction to complete the online temperature compensation.

[0087] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention. The scope of the invention is defined by the appended claims and their equivalents, all of which should be included within the scope of protection of the invention.

Claims

1. A method for temperature modeling and compensation of fiber optic gyroscopes based on dual temperature sensors, characterized in that, The method comprises the following steps: Step S1, collecting temperature data based on the first temperature sensor and the second temperature sensor fixed on the inside and outside of the fiber coil base, subtracting the measurement value of the first temperature sensor at the current time from the measurement value at the previous preset time to obtain the time gradient T'(n) of the fiber coil temperature; and subtracting the measurement values of the first temperature sensor and the second temperature sensor at the same time to obtain the spatial gradient ΔT(n) of the fiber coil temperature as the input information of the fiber gyroscope temperature model; Step S2, fixing the fiber gyroscope in a high-low temperature box, setting the collection parameters, starting the gyroscope under room temperature conditions, starting the temperature box after the gyroscope temperature is stable, setting the collection conditions and recording the data, finally obtaining sample data, and obtaining the fiber gyroscope output curve, the temperature output curve and the temperature change rate curve; Step S3, according to the output data characteristics of the fiber gyroscope, the data obtained in step S2 is divided into nine segments; Step S4, using the segmented gyroscope full-temperature experiment data to perform multiple linear regression parameter fitting on each segment of data, obtaining the model parameters under the corresponding temperature environment, and establishing the fiber gyroscope temperature model; Step S5, presetting parameters, collecting the original output of the gyroscope, calculating the gyroscope calibration factor at each temperature, and performing polynomial fitting on the calibration factor to reduce the nonlinearity of the calibration factor; Step S6, pre-processing the collected temperature data, obtaining the time gradient and the spatial gradient of the temperature by subtraction, and calculating the real-time zero bias temperature compensation amount in the fiber gyroscope temperature model calculated in step S4, and then performing temperature compensation reduction to complete the online temperature compensation.

2. The method according to claim 1, wherein, In step S1, the first temperature sensor and the second temperature sensor are both 18B20 temperature sensors, and are fixed on the inside and the outer wall of the symmetric position of the fiber coil base, respectively. The first temperature sensor is installed inside the fiber coil, and the second temperature sensor is installed on the outer wall of the fiber coil.

3. The method according to claim 2, wherein, The specific steps of collecting temperature data in step S1 include: The time gradient T'(n) of the fiber coil temperature and the spatial gradient ΔT(n) of the fiber coil temperature are as follows: T ′ (n) = T1(n) - T1(n-1); ΔT(n) = T1(n) - T2(n); Wherein, T1(n) and T2(n) are the measurement values of the first temperature sensor and the second temperature sensor at time n, respectively.

4. The method according to claim 1, wherein, The specific steps in step S2 include: Fixing the fiber gyroscope in a high-low temperature box, the sampling frequency of the gyroscope is 100 Hz, the temperature sampling period is 1 s, and the temperature change rate is set to 1° / min; Starting the gyroscope under room temperature conditions, starting the temperature box after the gyroscope temperature is stable, reducing the temperature in the temperature box to-40℃ and making the gyroscope work at this temperature for 90 minutes, then increasing the temperature in the temperature box to 60℃ and making the gyroscope work at this temperature for 90 minutes, and then reducing the temperature in the temperature box to room temperature, ending the test after the output of the fiber gyroscope reaches stability again; Performing 100ms smoothing processing on the output data of the fiber gyroscope, obtaining the output data of the fiber gyroscope, then calculating the temperature change rate, obtaining sample data, and obtaining the fiber gyroscope output curve, the temperature output curve, and the temperature change rate curve.

5. The method of claim 1, wherein the temperature modeling and compensation method is based on a dual temperature sensor fiber optic gyroscope. The specific steps in the step S4 include: In the model parameter fitting, the full-temperature test data of the fiber optic gyroscope is segmented according to different temperature conditions, and then the parameter fitting of multivariate linear regression is carried out by using each segment of data, so as to obtain the model parameters under the corresponding temperature environment; In the compensation, each related variable is calculated in real time, the data segment is determined, and then the corresponding model parameters are called to carry out the compensation calculation, and the temperature polynomial model is as follows: where L0 is a constant term, T is a relative temperature, dT / dt is a rate of change, A i and B j are polynomial coefficients, ε is a random error, and i and j are the highest orders.

6. The method of claim 1, wherein the temperature modeling and compensation method is based on a dual temperature sensor fiber optic gyroscope. The specific steps in the step S5 include: The fiber optic gyroscope is fixed in a high-low temperature box with a turntable, the sensitive axis of the gyroscope is parallel to the rotating shaft of the turntable, and the experimental temperature is set at six temperature points of-40 DEG C, -20 DEG C, 0 DEG C, +20 DEG C, +40 DEG C and +60 DEG C; After the internal temperature of the gyroscope is stabilized at each set temperature, the turntable is rotated in turn, the angular velocity is ± 2.5 ° / s, ± 4 ° / s, ± 6.4 ° / s, ± 10 ° / s, ± 15 ° / s, ± 30 ° / s, ± 45 ° / s and ± 60 ° / s respectively, the original output of the gyroscope is collected, the calibration factor of the gyroscope at each temperature is calculated, and the calibration factor is fitted by a polynomial.

7. The method according to claim 1, wherein, The specific steps in the step S6 include: Based on the single-chip microcomputer, the collected temperature data is preprocessed first, the time gradient and the space gradient of the temperature are obtained by subtraction, and then the fiber optic gyroscope temperature model calculated in the step S3 is substituted into the fiber optic gyroscope temperature model calculated in the step S3, so as to obtain the real-time zero bias temperature compensation amount, the data is sent to the FPGA for temperature compensation reduction, so as to realize the online temperature compensation.

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