Disassembly-free online self-calibration double-axis laser gyroscope strapdown inertial navigation implementation method

Abstract

The invention relates to a disassembly-free online self-calibration double-shaft laser gyroscope strapdown inertial navigation implementation method, which designs a modulation working mode based on double-shaft rotation, according to the design, a double-shaft rotating mechanism is additionally arranged on an inertial navigation unit, and the inertial navigation unit respectively rotates around three gyroscope sensitive shafts by utilizing an outer horizontal shaft and an inner azimuth shaft; exciting a navigation error generated by a scale factor error and an installation error of the laser gyroscope; sensitive shafts of the three accelerometers are enabled to point to the sky respectively, and navigation errors generated by scale factor errors, installation errors and zero positions of the accelerometers are excited; and then obtaining the navigation errors by taking external reference information as a benchmark, establishing an error relation model between the navigation errors and parameters needing to be calibrated, and completing estimation of each calibration parameter by adopting a Kalman filtering algorithm, so as to realize disassembly-free online self-calibration of the double-shaft laser gyroscope strapdown inertial navigation.

Description

Technical Field

[0001] The present invention relates to a method for realizing a dual-axis laser gyro strapdown inertial navigation system with no-disassembly online self-calibration, belonging to the technical field of inertial navigation. Background Art

[0002] In recent years, marine inertial navigation systems have undergone a significant transformation, from liquid-floating quartz electromechanical gyro platforms to laser gyro strapdown inertial navigation systems. Inertial navigation equipment is evolving toward miniaturization, intelligence, and high precision. Strapdown laser gyro systems require regular calibration of key inertial component parameters to ensure the accuracy of their output data. However, this calibration process requires the removal of the core inertial group (IAG) and installation on a calibration platform. Disassembly and installation inevitably introduce errors, and coordinate alignment is required after each calibration. In certain applications requiring extremely accurate attitude data and long-term inertial navigation support, disassembly, calibration, and repeated installation clearly cannot meet these requirements. Summary of the Invention

[0003] The purpose of the present invention is to overcome the deficiencies of the prior art and propose a method for realizing a dual-axis laser gyro strapdown inertial navigation system with disassembly-free online self-calibration. This method can eliminate the need for disassembly of the inertial navigation core components in conventional calibration methods, reduce the errors introduced by disassembly and installation, and eliminate the corresponding coordinate alignment process. The method has high application value in the field of high-precision inertial navigation.

[0004] The technical solution adopted by the present invention to solve the above-mentioned problems is: a method for realizing a dual-axis laser gyro strapdown inertial navigation system with online self-calibration without disassembly, combining a calibration platform with a strapdown inertial navigation system, designing a laser gyro strapdown inertial navigation system with rotation modulation based on a dual-axis frame system, using an outer horizontal axis and an inner azimuth axis to make the inertial system rotate around the three gyro sensitive axes respectively, stimulating the navigation error caused by the laser gyro scale factor error and installation error; making the three accelerometer sensitive axes point to the sky respectively, stimulating the navigation error caused by the accelerometer scale factor error, installation error and zero position; then obtaining these navigation errors based on external reference information, establishing an error relationship model between the navigation error and the parameters to be calibrated, and using the Kalman filter algorithm to complete the estimation of each calibration parameter, thereby realizing the online self-calibration without disassembly of the dual-axis laser gyro strapdown inertial navigation system. The method comprises the following steps:

[0005] Step 1: Disassembly-free online self-calibration algorithm

[0006] Disassembly-free online self-calibration means that when the ship is docked at the dock, there is no need to perform any hardware operations on the inertial navigation equipment. Just send a command and the inertial navigation equipment's own rotation mechanism and algorithm can be used to calibrate all inertial component parameters.

[0007] 1) The angular velocity of the Earth's rotation and the angular velocity of the navigation system (n system):

[0008] Projection of the Earth's rotation angular velocity in the navigation system (n system):

[0009]

[0010] In formula (1): is the projection of the Earth's rotational angular velocity in the navigation system (n system), ω ie is the angular velocity of the Earth's rotation, and L is the latitude of the origin of the navigation system (n system).

[0011] right Finding the deviation yields

[0012]

[0013] In formula (2): is the projection of the Earth's rotation angular velocity error in the navigation system (n system), ω ie is the angular velocity of the Earth’s rotation, and δL is the latitude error of the origin of the navigation system (n system).

[0014] The angular velocity of the navigation system (n system) is shown as follows:

[0015]

[0016] In formula (3): is the projection of the angular velocity of the navigation system (n system) under the navigation system (n system), V N The projection of the north linear velocity output by the inertial navigation system (n system), V E The projection of the eastward linear velocity output by the inertial navigation system (n system), R M Represent the principal curvature radius of the meridian, R N represents the main curvature radius of the azimuth circle, and h is the height of the inertial navigation unit relative to the sea level.

[0017] right Finding the deviation yields

[0018]

[0019] In formula (4): is the angular velocity error of the navigation system (n system), δV N The projection of the north linear velocity output by the inertial navigation system in the navigation system (n system), δV E The projection of the north linear velocity output by the inertial navigation system in the navigation system (n system). The definitions of other symbols are as follows: Equation (2) and Equation (3).

[0020] 2. Attitude error equation:

[0021]

[0022] φ n =[φ E φ N φ U ] T is the attitude angle error, where E represents the east direction, N represents the north direction, and U represents the sky direction. is the angular velocity of the inertial navigation rotating coordinate system (p system), They represent the 3*3 transformation matrix from the inertial navigation rotating coordinate system (p system) to the navigation coordinate system (n system), and the rest of the symbols are defined in the same way as in (3) and (5).

[0023] 3. Speed error equation:

[0024]

[0025] In formula (6), δV n =[δV E δV N δV U ] T is the projection of the inertial velocity error in the navigation system (n system), f n =[f E f N f U ] T is the projection of the inertial navigation accelerometer specific force measurement value in the navigation system (n system), is the measurement error of the inertial accelerometer specific force, They represent the 3*3 transformation matrix from the inertial navigation rotation coordinate system (p system) to the navigation coordinate system (n system), δg n represents the gravity error, and the definitions of other symbols are as shown in Equations (2), (3), (4), and (5).

[0026] 3. Position error equation

[0027]

[0028] In formula (8), δL is the inertial navigation latitude error, δλ is the inertial navigation longitude error, δh is the inertial navigation height error, V N The projection of the north linear velocity output by the inertial navigation system (n system), V E The projection of the eastward linear velocity output by the inertial navigation system in the navigation system (n system), δV N The projection of the north linear velocity error output by the inertial navigation system in the navigation system (n system), δV E The projection of the eastward linear velocity error output by the inertial navigation system in the navigation system (n system), L is the latitude output by the inertial navigation system, R M Represent the principal curvature radius of the meridian, RN represents the main curvature radius of the azimuth circle, and h is the height output by the inertial navigation.

[0029] 4. The error model of the laser inertial navigation inertial measurement device is as follows:

[0030]

[0031] In formula (9): represents the measurement error of the gyroscope, Indicates the measurement value of the gyroscope, ε indicates the added constant measurement zero drift of the gyroscope, δK g =diag[δK gx δK gy δK gz ] represents the scale factor error of the gyroscope, Indicates the installation error of the gyroscope.

[0032]

[0033] In formula (10): Indicates the error in the inertial accelerometer specific force measurement value, Indicates the added constant measurement bias of the accelerometer, δK a =diag[δK ax δK ay δK az ] represents the scale factor error of the accelerometer, Indicates the installation error of the accelerometer.

[0034] The specific form is as follows:

[0035]

[0036] In formula (11): δK gx Denotes the scale factor error of the x-axis gyroscope, δK gy Denotes the scale factor error of the y-axis gyroscope, δK gz Indicates the scale factor error of the z-axis gyroscope. gxy U gxz U gyx U gyz U gzx U gzy ]The 6 error parameters represent the installation error coefficients of the gyroscope.

[0037] The specific form is as follows:

[0038]

[0039] In formula (12): δKax Scale factor error of the x-axis accelerometer, δK ay Scale factor error of the y-axis accelerometer, δK az Scale factor error of the z-axis accelerometer. axy U axz U ayx U ayz U azx U azy ]The 6 error parameters represent the installation error coefficients of the accelerometer.

[0040] According to this method of defining the installation error, the laser gyro and accelerometer will generate 12 installation error angles. Due to the insufficient constraints of the carrier coordinate system, the 12 installation error angles cannot be fully decoupled. Therefore, in order to make all the installation errors uniquely determined, this paper imposes the following constraints: the x-axis of the carrier coordinate system coincides with the x-direction sensitive axis of the inertial navigation gyro, and the y-axis of the carrier coordinate system is located in the plane formed by the x-direction sensitive axis and the y-direction sensitive axis of the inertial navigation gyro. After the constraints, the laser gyro installation error parameter U gxy =U gxz =U gyz =0.

[0041] Since δK gx , δK gy , δK gz , δK ax , δK ay , δK az , U gxy , U gxz , U gyx , U gyz , U gzx , U gzy , U axy , U axz , U ayx , U ayz , U azx , U azy is a constant, and its derivative can be obtained as follows:

[0042]

[0043] δK gI =[δK gx δK gy δK gz ] T (14)δK gI =[δK gx δK gy δK gz ] T (15)

[0044] U gII =[U gxy U gxz U gyx U gyz U gzx U gzy ] T (16)

[0045] U gII =[U axy U axz U ayx U ayz U azx U azy ] T (17).

[0046] Step 2: Filter Design

[0047] 1. Selection of state variables

[0048] To realize the online self-calibration of the dual-axis laser strapdown inertial navigation system, the state variable X is selected as follows:

[0049]

[0050] In formula (18): E They represent the east misalignment angle error of the inertial navigation, φ N They represent the inertial navigation north misalignment angle error, φ U They represent the inertial navigation celestial misalignment angle error, δV E Indicates the eastward velocity error of the inertial navigation, δV N Indicates the north velocity error of the inertial navigation, δV U represents the inertial navigation celestial velocity error, δL represents the inertial navigation latitude error, δλ represents the inertial navigation longitude error, δh represents the inertial navigation height error, ε x is the constant drift of the inertial navigation x-axis gyroscope, ε y is the constant drift of the inertial navigation y-axis gyroscope, ε z is the constant drift of the inertial navigation z-axis gyroscope, δK gx Scale factor error of the inertial navigation x-axis gyroscope, δK gy The scale factor error of the inertial navigation y-axis gyroscope, inertial navigation δK gz Scale factor error of the z-axis gyroscope, U gxy The angle between the x-direction sensitive axis of the gyroscope in the inertial navigation and the xoz plane of the carrier coordinate system, U gxz The angle between the x-direction sensitive axis of the gyroscope in the inertial navigation and the xoy plane of the carrier coordinate system, U gyx The angle between the y-direction sensitive axis of the gyroscope in the inertial navigation and the yoz plane of the carrier coordinate system, U gyzThe angle between the y-direction sensitive axis of the gyroscope in the inertial navigation and the yox plane of the carrier coordinate system, U gzx The angle between the sensitive axis of the gyroscope in the z direction and the zoy plane of the carrier coordinate system, U gzy The angle between the sensitive axis of the gyroscope in the z direction and the zox plane of the carrier coordinate system in the inertial navigation system, is the constant measurement zero bias of the inertial navigation x-axis accelerometer, is the constant measurement zero bias of the inertial navigation y-axis accelerometer, is the constant measurement bias of the inertial navigation z-axis accelerometer, δK ax Scale factor error of the inertial navigation x-axis accelerometer, δK ay Scale factor error of the inertial navigation y-axis accelerometer, δK az Scale factor error of the inertial navigation z-axis accelerometer, U axy The angle between the sensitive axis in the x-direction of the inertial accelerometer and the xoz plane of the carrier coordinate system, U axz The angle between the sensitive axis in the x-direction of the inertial accelerometer and the xoy plane of the carrier coordinate system, U ayx The angle between the sensitive axis in the y direction of the inertial accelerometer and the yoz plane of the carrier coordinate system, U ayz The angle between the sensitive axis in the y direction of the inertial accelerometer and the yox plane of the carrier coordinate system, U azx The angle between the sensitive axis in the z direction of the inertial accelerometer and the zoy plane of the carrier coordinate system, U azy The angle between the sensitive axis in the z direction of the inertial accelerometer and the ZOX plane of the carrier coordinate system.

[0051] 2. Selection of observed variables

[0052] Since the attitude reference cannot be provided during the online calibration process, the attitude error cannot be measured. The speed and position of the laser strapdown inertial navigation system can be based on the GPS measurement value as a reference. The observation quantities selected in this paper are:

[0053] Z=[V I -V GPS P I -P GPS ] (19)

[0054] Among them [V I P I ] are the speed and position outputs of the dual-axis laser strapdown inertial navigation system, [V GPS P GPS ] are the speed and position outputs of GPS respectively.

[0055] 3. Kalman filter establishment

[0056] The system equation and measurement equation of the Kalman filter are as follows:

[0057]

[0058] Where: F(t) is the system matrix, obtained from equations (1) to (17); H(t) is the measurement matrix, obtained from equation (18); W(t) is the system noise, and V(t) is the measurement noise. The system matrix and measurement matrix are directly related to the error measurement model, which can be expanded as follows:

[0059]

[0060] In formula (21), F1, F21, F22, and F3 are self-defined matrices with no specific meaning. They can be obtained from formulas (5), (6), (7), (8), (9), and (10). i×j is a matrix with i rows and j columns and 0.

[0061]

[0062] In formula (22): I i×i is the i-order unit matrix, 0 i×j is a matrix with i rows and j columns and 0.

[0063] Step 3: Design of online self-calibration sequence without disassembly

[0064] The inertial navigation system adopts a 21-position online self-calibration sequence, as shown in Table 1.

[0065] Using a dual-axis rotation scheme, in which the inner azimuth axis and the outer horizontal axis rotate sequentially, all inertial component errors can be modulated, thereby achieving higher autonomous navigation accuracy. The dual-axis rotation scheme is shown in Figure 1. The x-, y-, and z-axes represent the gyroscope's sensitive axes, and the three axes point to the orientation of each element in the sequence ENU, EUS, ESD, EDN, ENU, EDN, ESD, EUS, UWN, NWU, DWN, SWD, DWN, NWU, UWS, WDS, DEN, WDN, UWS, EUS, and ENU, respectively. E, W, N, S, U, and D represent the six directions of east, west, north, south, celestial, and terrestrial in the geographic coordinate system, respectively. The online self-calibration sequence is shown in Table 1.

[0066] Table 1 Sequence of online self-calibration without disassembly

[0067]

[0068] Compared with the prior art, the present invention has the following advantages:

[0069] 1) The present invention designs an error model of laser inertial navigation inertial measurement device by integrating attitude error, velocity error and position error, and proposes a disassembly-free online self-calibration algorithm for dual-axis laser gyro strapdown inertial navigation.

[0070] 2) The present invention aims at the disassembly-free online self-calibration algorithm of the dual-axis laser gyro strapdown inertial navigation system, and establishes the system equation and measurement equation of the Kalman filter by selecting state variables and observation variables.

[0071] 3) The present invention adopts a 21-position online self-calibration sequence and a dual-axis rotation mode in which the inner azimuth axis and the outer horizontal axis rotate in sequence to modulate all inertial component errors, thereby achieving higher autonomous navigation accuracy.

[0072] 4) The present invention can eliminate the need to disassemble the core components of the inertial navigation system in ordinary calibration methods, reduce the errors introduced by disassembly and installation, and at the same time save the corresponding coordinate alignment process, which has high application value in the field of high-precision inertial navigation. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] FIG1 is a diagram of the online self-calibration sequence of the dual-axis rotation mode of the present invention; Figure 1-1 Indicates the order 1-4, Figure 1-2 Indicates the order 5-8, Figure 1-3 Indicates the order 9-12, Figure 1-4 Indicates the order 13-16, Figure 1-5 Indicates the order 17-20.

[0074] Figure 2 This is a scene diagram of a static online self-calibration test in an embodiment of the present invention.

[0075] FIG3 is a graph showing attitude error curves (rms is root mean square) of the inertial navigation system A in the single-axis rotation mode according to an embodiment of the present invention. Figure 3-1 , 3-2, 3-3.

[0076] Figure 4 is a positioning error curve diagram of the inertial navigation A in the single-axis rotation mode according to the embodiment of the present invention, which are respectively Figure 4-1 , 4-2, 4-3.

[0077] FIG5 is an attitude error curve (rms is root mean square) of the inertial navigation B in the dual-axis rotation mode according to an embodiment of the present invention, which are Figure 5-1 , 5-2, 5-3.

[0078] FIG6 is a positioning error curve diagram of the inertial navigation device in the dual-axis rotation mode according to an embodiment of the present invention, which are Figure 6-1 , 6-2, 6-3.

[0079] Figure 7 is a graph of attitude error during the inertial navigation information fusion test voyage (rms is root mean square) according to an embodiment of the present invention, which are Figure 7-1 , 7-2, 7-3. DETAILED DESCRIPTION

[0080] The present invention will be described in further detail below with reference to the accompanying drawings and embodiments.

[0081] Example:

[0082] 1. Static experiment

[0083] The inertial measurement device of the inertial navigation equipment is placed on the static base in the laboratory to complete the startup and perform static online self-calibration. Figure 2 Static online self-calibration was performed 6 times to assess the repeatability of the self-calibrated inertial navigation parameters. Error statistics were evaluated based on the standard deviation of the calibration results. The test results of online self-calibration under static conditions are shown in Table 2.

[0084] Table 2 Online self-calibration test results of inertial navigation equipment under static conditions (part of the data is normalized)

[0085]

[0086] 2 Dynamic test

[0087] The inertial measurement unit (IMU) of the inertial navigation system was placed on a laboratory rocking table and started up. Dynamic online self-calibration was performed under conditions simulating a ship moored at a dock (with a rocking amplitude of less than 1°). Static online self-calibration was performed six times to assess the repeatability of the self-calibrated IMU parameters. Error statistics were evaluated based on the standard deviation of the calibration results. The results of the online self-calibration test under static conditions are shown in Table 3.

[0088] Table 3 Online self-calibration test results of inertial navigation equipment under dynamic conditions (part of the data is normalized)

[0089]

[0090] 3. Static / dynamic verification comparison

[0091] The comparison of the online self-calibration test results of the inertial navigation equipment under static and dynamic conditions is shown in Table 4.

[0092] Table 4 Comparison of online self-calibration test results of inertial navigation equipment under static and dynamic conditions

[0093]

[0094]

[0095] The test results show that the comparison between the mean value of the static test results and the mean value of the dynamic test results meets the error requirements of the disassembly-free online self-calibration, proving that the disassembly-free online self-calibration technology can enable the inertial navigation equipment to realize the inertial navigation parameter self-calibration function online under ship installation conditions, and the self-calibration repeatability under static / dynamic conditions (sway amplitude within 1°) meets the design requirements.

[0096] The INS information fusion test was conducted for a cumulative 48 hours. Error statistics were calculated using the longitude and latitude of the test platform as the ship's position reference and the attitude output of the platform as the attitude reference.

[0097] The attitude and positioning error curves of INS A in single-axis rotation mode are shown in Figures 3 and 4, the attitude and positioning error curves of INS B in dual-axis rotation mode are shown in Figures 5 and 6, and the attitude error curve of the INS information fusion test voyage is shown in Figure 7.

[0098] The statistical results of the 48-hour verification test of inertial navigation information fusion technology are shown in Table 5.

[0099] Table 5 Results of 48-hour verification test of multi-inertial navigation information fusion technology

[0100]

[0101] Experimental data shows that after Kalman filtering information fusion of single-axis and dual-axis rotation modulation strapdown inertial navigation systems, the fused data has horizontal attitude angle accuracy comparable to that of the single-axis mode, positioning accuracy comparable to that of the dual-axis mode, and heading accuracy improved compared to both single-axis and dual-axis modes. This demonstrates that the fused data fully combines the advantages of both modes, resulting in higher precision autonomous navigation.

[0102] In addition to the above embodiments, the present invention also includes other implementation methods. Any technical solutions formed by equivalent transformation or equivalent replacement should fall within the scope of protection of the claims of the present invention.

Claims

1. A method for realizing a dual-axis laser gyro strapdown inertial navigation system with no-disassembly online self-calibration, characterized by: The method is based on a dual-axis rotation modulation working mode. This design adds a dual-axis rotation mechanism to the inertial navigation system. Using the outer horizontal axis and the inner azimuth axis, the system rotates around the three gyro-sensitive axes to stimulate navigation errors caused by laser gyro scale factor errors and installation errors. The sensitive axes of the three accelerometers are pointed upwards to stimulate navigation errors caused by the scale factor error, installation error and zero position of the accelerometers. These navigation errors are then obtained based on external reference information. By establishing an error relationship model between the navigation errors and the parameters to be calibrated, the Kalman filter algorithm is used to estimate the calibration parameters, thus realizing the disassembly-free online self-calibration of the dual-axis laser gyro strapdown inertial navigation system.

2. The method for realizing a dual-axis laser gyro strapdown inertial navigation system with no-disassembly online self-calibration according to claim 1, characterized in that: The method specifically comprises the following steps: Step 1: Disassembly-free online self-calibration algorithm Disassembly-free online self-calibration means that when the ship is docked at the dock, there is no need to perform any hardware operations on the inertial navigation equipment. Just send a command, and the inertial navigation equipment's own rotation mechanism and algorithm will be used to calibrate all inertial component parameters. In order to uniquely determine all installation errors, the x-axis of the carrier coordinate system is aligned with the x-sensitive axis of the inertial gyro, and the y-axis of the carrier coordinate system is located in the plane formed by the x-sensitive axis and the y-sensitive axis of the inertial gyro. After the constraints are applied, the laser gyro installation error parameters are eliminated. Step 2: Filter Design 1) Selection of state variables To realize the online self-calibration of the dual-axis laser strapdown inertial navigation system, the state variable X is selected as follows: 2) Selection of observed variables The speed and position of the laser strapdown inertial navigation system can be based on the GPS measurement values and the following observation variables are selected: Z=[V I -V GPS P I -P GPS ] Among them [V I P I ] are the speed and position outputs of the dual-axis laser strapdown inertial navigation system, [V GPS P GPS ] are the speed and position output of GPS respectively; 3) Kalman filter establishment The system equations and measurement equations of the Kalman filter are shown below: Where: F(t) is the system matrix, obtained from equations (1) to (17); H(t) is the measurement matrix, obtained from equation (18); W(t) is the system noise, and V(t) is the measurement noise. Step 3: Design of online self-calibration sequence without disassembly The inertial navigation institute adopts a 21-position online self-calibration sequence and a dual-axis rotation mode in which the inner azimuth axis and the outer horizontal axis rotate in sequence to modulate all inertial component errors, thereby achieving higher autonomous navigation accuracy. The x-axis, y-axis, and z-axis represent the sensitive axes of the gyroscope, and the three axes point to the directions corresponding to the sequential positions of each group of elements in the sequence ENU, EUS, ESD, EDN, ENU, EDN, ESD, EUS, UWN, NWU, DWN, SWD, DWN, NWU, UWS, WDS, DEN, WDN, UWS, EUS, and ENU, respectively. Among them, E, W, N, S, U, and D represent the six directions of east, west, north, south, celestial, and terrestrial in the geographic coordinate system, respectively.

3. The method for realizing a dual-axis laser gyro strapdown inertial navigation system with no-disassembly online self-calibration according to claim 2, characterized in that: In step 2, the state variable X is selected as follows: Where: φ E Indicates the inertial navigation east misalignment angle error, φ N Indicates the inertial navigation north misalignment angle error, φ U They represent the inertial navigation celestial misalignment angle error, δV E Indicates the eastward velocity error of the inertial navigation, δV N Indicates the north velocity error of the inertial navigation, δV U represents the inertial navigation celestial velocity error, δ L represents the inertial navigation latitude error, δλ represents the inertial navigation longitude error, δh represents the inertial navigation height error, ε x is the constant drift of the inertial navigation x-axis gyroscope, ε y is the constant drift of the inertial navigation y-axis gyroscope, ε z is the constant drift of the inertial navigation z-axis gyroscope, δK gx Scale factor error of the inertial navigation x-axis gyroscope, δK gy The scale factor error of the inertial navigation y-axis gyroscope, inertial navigation δK gz Scale factor error of the z-axis gyroscope, U gxy The angle between the x-direction sensitive axis of the gyroscope in the inertial navigation and the xoz plane of the carrier coordinate system, U gxz The angle between the x-direction sensitive axis of the gyroscope in the inertial navigation and the xoy plane of the carrier coordinate system, U gyx The angle between the y-direction sensitive axis of the gyroscope in the inertial navigation and the yoz plane of the carrier coordinate system, U gyz The angle between the y-direction sensitive axis of the gyroscope in the inertial navigation and the yox plane of the carrier coordinate system, U gzx The angle between the sensitive axis of the gyroscope in the z direction and the zoy plane of the carrier coordinate system, U gzy The angle between the sensitive axis of the gyroscope in the z direction and the zox plane of the carrier coordinate system in the inertial navigation system, is the constant measurement zero bias of the inertial navigation x-axis accelerometer, is the constant measurement zero bias of the inertial navigation y-axis accelerometer, is the constant measurement bias of the inertial navigation z-axis accelerometer, δK ax Scale factor error of the inertial navigation x-axis accelerometer, δK ay Scale factor error of the inertial navigation y-axis accelerometer, δK az Scale factor error of the inertial navigation z-axis accelerometer, U axy The angle between the sensitive axis in the x-direction of the inertial accelerometer and the xoz plane of the carrier coordinate system, U axz The angle between the sensitive axis in the x-direction of the inertial accelerometer and the xoy plane of the carrier coordinate system, U ayx The angle between the sensitive axis in the y direction of the inertial accelerometer and the yoz plane of the carrier coordinate system, U ayz The angle between the sensitive axis in the y direction of the inertial accelerometer and the yox plane of the carrier coordinate system, U axz The angle between the sensitive axis in the z direction of the inertial accelerometer and the zoy plane of the carrier coordinate system, U azy The angle between the sensitive axis in the z direction of the inertial accelerometer and the ZOX plane of the carrier coordinate system.

4. The method for realizing a dual-axis laser gyro strapdown inertial navigation system with no-disassembly online self-calibration according to claim 2, characterized in that: The system matrix and measurement matrix in step 2 are directly related to the error measurement model, which can be expanded as follows: In formula (21): F1, F21, F22, F3 are custom matrices with no specific meaning. i×j is a matrix with i rows and j columns and 0; Where: I i×i is the i-order unit matrix, O i×j is a matrix with i rows and j columns and 0.

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