Vehicle-mounted IMU (Inertial Measurement Unit) installation angle estimation method and system based on Gaussian Newton iteration

Abstract

The invention provides a vehicle-mounted IMU installation angle estimation method and system based on Gauss-Newton iteration, and relates to the technical field of navigation positioning, and the method comprises the steps: constructing a Gauss-Newton iteration objective function of IMU installation angle estimation; initializing a rotation matrix into a third-order unit matrix, and performing first-order Taylor expansion on the Gaussian-Newton iteration objective function to obtain a Jacobian matrix corresponding to the Gaussian-Newton iteration objective function; establishing a linear least square relational expression based on the Jacobian matrix to obtain a constraint equation containing a Hessian matrix and a bias matrix; iteratively executing the solving of the Jacobian matrix, the construction of the Hessian matrix and the offset matrix and the updating operation of the conversion matrix until the Gaussian Newton iteration objective function for IMU installation angle estimation is converged, and determining the conversion matrix obtained by the last iteration as the optimal rotation matrix; and according to the matrix elements in the optimal rotation matrix, calculating through an inverse trigonometric function to obtain an optimal pitching installation angle and an optimal course installation angle.

Description

Technical Field

[0001] The present invention relates to a vehicle-mounted navigation and positioning technology, and in particular to a vehicle-mounted IMU installation angle estimation method and system based on Gauss-Newton iteration. Background Art

[0002] Nonholonomic constraints and odometry have been shown to significantly improve the accuracy of in-vehicle integrated navigation when GNSS signals are unavailable. However, in practical applications, the IMU's carrier coordinate system is at an angle to the vehicle coordinate system where the odometry resides. This can lead to significant deviations in the position and attitude information output by the navigation system, compromising navigation accuracy and reliability. Therefore, accurately estimating the IMU's mounting angle is a key approach to improving in-vehicle integrated navigation.

[0003] Currently, methods for estimating the installation angle of an on-board IMU are mainly divided into offline estimation methods and online estimation methods. For example, the published patent CN117516592A provides a method, device, electronic device, and storage medium for estimating the installation angle of an on-board IMU. This method estimates the installation angle of the on-board IMU based on the attitude angles of the on-board IMU in two states. However, this method is an offline estimation method, and the estimation accuracy is limited by the degree of overlap between the vehicle's original head direction after turning around. The published patent CN116519018A provides a method, system, and medium for online estimation of the installation angle error of a low-cost embedded integrated navigation system on a vehicle. This method saves the integrated navigation data and uses the current vehicle's speed relationship in the V and B frames to obtain the final estimated installation angle. However, this method requires saving the heading angle and pitch angle, then removing the maximum and minimum values of the two, and then averaging the remaining data to obtain the final estimated IMU installation angle. Therefore, the accuracy of the IMU installation angle estimation by this method is limited.

[0004] Therefore, in order to achieve high-precision vehicle-mounted IMU installation angle estimation in real-time systems, it is necessary to comprehensively consider the vehicle-mounted IMU installation angle estimation accuracy and algorithm complexity to achieve high-precision vehicle-mounted IMU installation angle estimation with low computing power requirements. Summary of the Invention

[0005] The embodiments of the present invention provide a vehicle-mounted IMU installation angle estimation method and system based on Gauss-Newton iteration, which can solve the problems in the prior art.

[0006] A first aspect of an embodiment of the present invention provides a method for estimating a vehicle-mounted IMU installation angle based on Gauss-Newton iteration, comprising: Constructing a Gauss-Newton iterative objective function for IMU installation angle estimation, the Gauss-Newton iterative objective function includes the true three-dimensional position information obtained from the fixed solution of the satellite navigation equipment, the integrated three-dimensional position information of the strapdown inertial navigation, and the rotation matrix from the carrier coordinate system to the vehicle coordinate system; initializing the rotation matrix to a third-order identity matrix, and performing a first-order Taylor expansion on the Gauss-Newton iterative objective function to obtain the Jacobian matrix corresponding to the Gauss-Newton iterative objective function; A linear least squares relationship is established based on the Jacobian matrix, and a constraint equation including a Hessian matrix and a bias matrix is obtained by differentiating the linear least squares relationship and setting the derivative to zero; solving the Jacobian matrix, constructing the Hessian matrix and the bias matrix, and updating the transformation matrix are iteratively performed until the Gauss-Newton iterative objective function of the IMU installation angle estimation converges, and the transformation matrix obtained from the last iteration is determined as the optimal rotation matrix; According to the matrix elements in the optimal rotation matrix, the optimal pitch installation angle and the optimal yaw installation angle are calculated by inverse trigonometric functions, wherein the optimal pitch installation angle is obtained by the inverse sine function of the elements in the third row and first column of the optimal rotation matrix, and the optimal yaw installation angle is obtained by the inverse tangent function of the elements in the third row and second column and the elements in the third row and third column of the optimal rotation matrix.

[0007] In an optional embodiment, The Gauss-Newton iterative objective function for constructing the IMU installation angle estimation includes: ; The Gauss-Newton iterative objective function for IMU installation angle estimation is used. By continuously adjusting the IMU installation angle to minimize the objective function, the accurate IMU installation angle can be obtained, and the estimation of the IMU installation angle can be completed. N is the number of points where the selected satellite navigation equipment is in a fixed solution state. is the real three-dimensional position information obtained from the i-th satellite fixed solution, To select the i-th satellite navigation fixed solution, the strapdown inertial navigation integrated three-dimensional position information is: is the rotation matrix from the carrier coordinate system to the vehicle coordinate system.

[0008] In an optional embodiment, Initialize the rotation matrix to a third-order identity matrix, and perform a first-order Taylor expansion on the Gauss-Newton iterative objective function to obtain the Jacobian matrix corresponding to the Gauss-Newton iterative objective function, including: The perturbation model is used to perform Lie group and Lie algebra transformation on the rotation matrix. By multiplying the rotation matrix by a small amount on the left and solving the Lie algebraic change rate relative to the small amount, the rotation matrix is derivatized to obtain the specific expression of the Jacobian matrix: ; in, is the rotation matrix Multiply a small amount on the left The corresponding Lie algebra is, is the rotation center of the IMU coordinate system.

[0009] In an optional embodiment, The Hessian matrix is the product of the Jacobian matrix and its transpose, and the bias matrix is the product of the Jacobian matrix and the objective function.

[0010] In an optional embodiment, The method further comprises: Substituting the Hessian matrix and the bias matrix into the incremental equation of the Gauss-Newton method to obtain the increment of the conversion matrix; The increment of the conversion matrix is substituted into the conversion matrix update formula to obtain the updated conversion matrix.

[0011] In an optional embodiment, Calculating the optimal pitch installation angle and the optimal yaw installation angle using inverse trigonometric functions based on the matrix elements in the optimal rotation matrix includes: Based on the optimal rotation matrix , convert to obtain the optimal pitch installation angle , and the optimal heading installation angle , its conversion expression is: ; For the optimal pitch installation angle, is the optimal heading installation angle, is the optimal rotation matrix The element in the first row and first column of is the optimal rotation matrix The element in the second row and first column of is the optimal rotation matrix The element in the third row and first column of is the optimal rotation matrix The element in the third row and second column of is the optimal rotation matrix The element in the third row and third column of .

[0012] In the second aspect of the embodiments of this application, Provides a vehicle-mounted IMU installation angle estimation system based on Gauss-Newton iteration, including: The first unit is used to construct a Gauss-Newton iterative objective function for IMU installation angle estimation, wherein the Gauss-Newton iterative objective function includes the real three-dimensional position information obtained by the fixed solution of the satellite navigation equipment, the three-dimensional position information of the strapdown inertial navigation integration, and the rotation matrix from the carrier coordinate system to the vehicle coordinate system; the rotation matrix is initialized to a third-order identity matrix, and a first-order Taylor expansion is performed on the Gauss-Newton iterative objective function to obtain the Jacobian matrix corresponding to the Gauss-Newton iterative objective function; The second unit is used to establish a linear least squares relationship based on the Jacobian matrix, and obtain a constraint equation including a Hessian matrix and a bias matrix by deriving the linear least squares relationship and setting the derivative to zero; iteratively performing the solution of the Jacobian matrix, the construction of the Hessian matrix and the bias matrix, and the update operation of the transformation matrix until the Gauss-Newton iterative objective function of the IMU installation angle estimation converges, and determining the transformation matrix obtained from the last iteration as the optimal rotation matrix; The third unit is used to calculate the optimal pitch installation angle and the optimal yaw installation angle through inverse trigonometric functions based on the matrix elements in the optimal rotation matrix, wherein the optimal pitch installation angle is obtained by the inverse sine function of the elements in the third row and first column of the optimal rotation matrix, and the optimal yaw installation angle is obtained by the inverse tangent function of the elements in the third row and second column and the elements in the third row and third column of the optimal rotation matrix.

[0013] In the third aspect of the embodiments of this application, An electronic device is provided, comprising: processor; a memory for storing processor-executable instructions; The processor is configured to call the instructions stored in the memory to execute the aforementioned method.

[0014] A fourth aspect of the embodiment of the present application, A computer-readable storage medium is provided, on which computer program instructions are stored, wherein the computer program instructions implement the aforementioned method when executed by a processor.

[0015] The present application provides a vehicle-mounted IMU installation angle estimation method based on Gauss-Newton iteration, which solves the problem of insufficient estimation accuracy of existing vehicle-mounted IMU installation angle estimation methods; the method first constructs a vehicle-mounted IMU installation angle estimation model based on Gauss-Newton iteration, and then solves the vehicle-mounted IMU installation angle estimation model based on Gauss-Newton iteration to obtain the optimal vehicle-mounted IMU installation angle. Experimental verification shows that this method has high reliability, strong versatility, high algorithm operation efficiency, simple operation, high accuracy and good practicality. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 Schematic diagram of the process of estimating the installation angle of a vehicle-mounted IMU based on Gauss-Newton iteration according to an embodiment of the present invention; Figure 2 This is the result diagram of estimating the vehicle IMU installation angle using the method of this application; Figure 3 It is the cumulative distribution function diagram of the horizontal position error of the vehicle-mounted integrated navigation; Figure 4 This is a structural diagram of a vehicle-mounted IMU installation angle estimation system based on Gauss-Newton iteration according to an embodiment of the present invention. DETAILED DESCRIPTION

[0017] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0018] The following specific embodiments are used to describe the technical solution of the present invention in detail. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0019] Figure 1 FIG. 1 is a flow chart of a method for estimating the installation angle of an on-board IMU based on Gauss-Newton iteration according to an embodiment of the present invention. Figure 1 As shown, the method includes: Constructing a Gauss-Newton iterative objective function for IMU installation angle estimation, the Gauss-Newton iterative objective function includes the true three-dimensional position information obtained from the fixed solution of the satellite navigation equipment, the integrated three-dimensional position information of the strapdown inertial navigation, and the rotation matrix from the carrier coordinate system to the vehicle coordinate system; initializing the rotation matrix to a third-order identity matrix, and performing a first-order Taylor expansion on the Gauss-Newton iterative objective function to obtain the Jacobian matrix corresponding to the Gauss-Newton iterative objective function; A linear least squares relationship is established based on the Jacobian matrix, and a constraint equation including a Hessian matrix and a bias matrix is obtained by differentiating the linear least squares relationship and setting the derivative to zero; solving the Jacobian matrix, constructing the Hessian matrix and the bias matrix, and updating the transformation matrix are iteratively performed until the Gauss-Newton iterative objective function of the IMU installation angle estimation converges, and the transformation matrix obtained from the last iteration is determined as the optimal rotation matrix; According to the matrix elements in the optimal rotation matrix, the optimal pitch installation angle and the optimal yaw installation angle are calculated by inverse trigonometric functions, wherein the optimal pitch installation angle is obtained by the inverse sine function of the elements in the third row and first column of the optimal rotation matrix, and the optimal yaw installation angle is obtained by the inverse tangent function of the elements in the third row and second column and the elements in the third row and third column of the optimal rotation matrix.

[0020] In an optional embodiment, The Gauss-Newton iterative objective function for constructing the IMU installation angle estimation includes: ; The Gauss-Newton iterative objective function for IMU installation angle estimation is used. By continuously adjusting the IMU installation angle to minimize the objective function, the accurate IMU installation angle can be obtained, and the estimation of the IMU installation angle can be completed. N is the number of points where the selected satellite navigation equipment is in a fixed solution state. is the real three-dimensional position information obtained from the i-th satellite fixed solution, To select the i-th satellite navigation fixed solution, the strapdown inertial navigation integrated three-dimensional position information is: is the rotation matrix from the carrier coordinate system to the vehicle coordinate system.

[0021] In an optional embodiment, Initialize the rotation matrix to a third-order identity matrix, and perform a first-order Taylor expansion on the Gauss-Newton iterative objective function to obtain the Jacobian matrix corresponding to the Gauss-Newton iterative objective function, including: The perturbation model is used to perform Lie group and Lie algebra transformation on the rotation matrix. By multiplying the rotation matrix by a small amount on the left and solving the Lie algebraic change rate relative to the small amount, the rotation matrix is derivatized to obtain the specific expression of the Jacobian matrix: ; in, is the rotation matrix Multiply a small amount on the left The corresponding Lie algebra is, is the rotation center of the IMU coordinate system.

[0022] In an optional embodiment, The Hessian matrix is the product of the Jacobian matrix and its transpose, and the bias matrix is the product of the Jacobian matrix and the objective function.

[0023] In an optional embodiment, The method further comprises: Substituting the Hessian matrix and the bias matrix into the incremental equation of the Gauss-Newton method to obtain the increment of the conversion matrix; The increment of the conversion matrix is substituted into the conversion matrix update formula to obtain the updated conversion matrix.

[0024] In an optional embodiment, Calculating the optimal pitch installation angle and the optimal yaw installation angle using inverse trigonometric functions based on the matrix elements in the optimal rotation matrix includes: Based on the optimal rotation matrix , convert to get the optimal pitch installation angle , and the optimal heading installation angle , its conversion expression is: ; For the optimal pitch installation angle, is the optimal heading installation angle, is the optimal rotation matrix The element in the first row and first column of is the optimal rotation matrix The element in the second row and first column of is the optimal rotation matrix The element in the third row and first column of is the optimal rotation matrix The element in the third row and second column of is the optimal rotation matrix The element in the third row and third column of .

[0025] Another specific embodiment of the present application is as follows: S1. Construct a vehicle-mounted IMU installation angle estimation model based on Gauss-Newton iteration. Its expression is: , Where, The Gauss-Newton iterative objective function for IMU installation angle estimation is used. By continuously adjusting the IMU installation angle to minimize the objective function, the accurate IMU installation angle can be obtained, and the estimation of the IMU installation angle can be completed. N is the number of points where the selected satellite navigation equipment is in a fixed solution state. is the real three-dimensional position information obtained from the i-th satellite fixed solution, To select the i-th satellite navigation fixed solution, the strapdown inertial navigation integrated three-dimensional position information is: is the rotation matrix from the carrier coordinate system to the vehicle coordinate system.

[0026] further, Expand the following expression: , Where, They are the pitch installation angle, roll installation angle, and heading installation angle respectively. It should be noted that the roll installation error angle has no effect on the odometer output and therefore cannot be estimated.

[0027] S2. Solve the vehicle-mounted IMU installation angle estimation model based on Gauss-Newton iteration.

[0028] The specific operation steps of step S2 are: S201, initialize Gauss-Newton iteration parameters ;in, is the rotation matrix, which is initialized to the 3rd-order identity matrix; S202. Calculate the Jacobian matrix : The vehicle-mounted IMU installation angle estimation model based on Gauss-Newton iteration constructed in step S1 is subjected to first-order Taylor expansion, and its expression is: , Where, It is for about The derivative of , which is a Jacobian matrix; is the rotation matrix increment; Since the rotation matrix is a 3rd-order square matrix, it is not possible to directly perform derivative operations on it. Based on this, this application converts the rotation matrix into a Lie algebra through the conversion relationship between Lie groups and Lie algebras, and then performs Gauss-Newton iteration to calculate the optimal rotation matrix. Using the perturbation model, the rotation matrix Multiply a small amount on the left, and then solve the rate of change of the Lie algebra relative to this small amount, which completes the rotation matrix The derivative of is: , Where, is the rotation matrix Multiply a small amount on the left The corresponding Lie algebra is, is the rotation center of the IMU coordinate system; S203. Calculate the Hessian matrix : The core goal of Gauss-Newton iteration is to find , making minimum; and then Transformed into the following linear least squares relationship: , Where, is the optimal rotation matrix increment; Through the above least squares relationship Taking the derivative and setting it to zero, we can get the following constraint equation: , In the above constraint equation, the Hessian matrix is the coefficient on the left side of the equal sign in the above formula, that is , bias matrix is the coefficient on the right side of the equal sign in the above formula, that is ; Then, the incremental equation of the Gauss-Newton method is obtained, which is expressed as follows: , According to the Jacobian matrix obtained in step S202 , respectively calculated and ; S204, calculate the increment of the conversion matrix ; The result calculated in step S203 and Substitute into the above incremental equation to calculate the increment of the transformation matrix ; S205, update the conversion matrix : The increment of the conversion matrix obtained in step S204 is Substitute into the transformation matrix update formula: , Where, is the updated transformation matrix, is the transformation matrix substituted into the current calculation process; S206, repeat the above steps S201 to S205 to iteratively update the conversion matrix until the vehicle-mounted IMU installation angle estimation model based on Gauss-Newton iteration constructed in step S2, that is, the vehicle-mounted IMU installation angle estimation function based on Gauss-Newton iteration is obtained. Reaching the convergence state; at this time, the increment of the current transformation matrix That is the optimal rotation matrix increment ; Then, based on the optimal rotation matrix increment , calculate the optimal rotation matrix , whose expression is: , where Substitute the transformation matrix substituted in the current iteration process; In step S206, the number of iterations is generally set to ≥100 times; S207: Based on the optimal rotation matrix obtained in step S206 , convert to get the optimal pitch installation angle , and the optimal heading installation angle , its conversion expression is: , Where, For the optimal pitch installation angle, is the optimal heading installation angle, is the optimal rotation matrix The element in the first row and first column of is the optimal rotation matrix The element in the second row and first column of is the optimal rotation matrix The element in the third row and first column of is the optimal rotation matrix The element in the third row and second column of is the optimal rotation matrix The element in the third row and third column of .

[0029] After the above steps S201 to S207, the vehicle-mounted IMU installation angle estimation based on Gauss-Newton iteration is completed.

[0030] In summary, this solution has the following advantages: A vehicle-mounted IMU installation angle estimation method based on Gauss-Newton iteration is provided, which solves the problem of insufficient estimation accuracy of existing vehicle-mounted IMU installation angle estimation methods. The method first constructs a vehicle-mounted IMU installation angle estimation model based on Gauss-Newton iteration, and then solves the vehicle-mounted IMU installation angle estimation model based on Gauss-Newton iteration to obtain the optimal vehicle-mounted IMU installation angle. Experimental verification shows that the method has high reliability, strong versatility, high algorithm operation efficiency, simple operation, high accuracy and good practicality.

[0031] like Figure 2 The figure shows the result of estimating the vehicle IMU installation angle using the method of this application. As can be seen from the figure, as the IMU installation angle estimation time increases, the number of iterations in the nonlinear optimization process also increases. Therefore, the estimated IMU installation angle gradually converges to the true value and eventually stabilizes.

[0032] like Figure 3 The figure shows the cumulative distribution function of the horizontal position error for vehicle-mounted integrated navigation using the method of the present application to compensate for the IMU installation angle, the ESKF method to compensate for the IMU installation angle, and the method without IMU installation angle compensation. As can be seen from the figure, the method of the present application minimizes the horizontal position error under the same probability, and therefore the vehicle-mounted IMU installation angle estimated using the method of the present application has the highest accuracy.

[0033] Furthermore, in order to verify the correctness of the present invention, actual measurement experiments were carried out; among them, the performance parameters of the gyroscope and accelerometer in the experiment are listed in Table 1, the performance parameters of the GPS module in the experiment are listed in Table 2, and the performance parameters of the wheel speed meter module in the experiment are listed in Table 3.

[0034] Table 1: Table 2: Table 3: Based on the data collected by the gyroscope and accelerometer with the performance parameters shown in Table 1, the GPS module with the performance parameters shown in Table 2, and the wheel speed meter with the performance parameters shown in Table 3, an experiment on estimating the installation angle of the vehicle-mounted IMU was carried out; the method of the present invention was used to estimate the installation angle of the vehicle-mounted IMU, and the ESKF method and the method without compensating the installation angle of the vehicle-mounted IMU were used as comparative examples.

[0035] In the experiment, the horizontal position error of vehicle-mounted integrated navigation was compared using the method of compensating the IMU installation angle using the method of this application, the ESKF method of compensating the IMU installation angle, and the method of not compensating the IMU installation angle, as shown in Table 4 below.

[0036] Table 4: The horizontal position error comparison in Table 4 shows that the method of the present invention, after compensating for the on-board IMU installation angle error, can achieve higher-precision positioning, thereby indicating that higher-precision on-board IMU installation angle estimation can be achieved. Compared with the method without compensating for the IMU installation angle, the horizontal position error was reduced by 32.5% after compensating for the on-board IMU installation angle error using the method of the present invention; compared with the method of compensating for the IMU installation angle error using the ESKF, the horizontal position error was reduced by 14.7% after compensating for the on-board IMU installation angle error using the method of the present invention. This verifies the effectiveness and correctness of the method provided by the present invention.

[0037] The second aspect of the present application provides a vehicle-mounted IMU installation angle estimation system based on Gauss-Newton iteration, such as Figure 4Shown, including: The first unit is used to construct a Gauss-Newton iterative objective function for IMU installation angle estimation, wherein the Gauss-Newton iterative objective function includes the real three-dimensional position information obtained by the fixed solution of the satellite navigation equipment, the three-dimensional position information of the strapdown inertial navigation integration, and the rotation matrix from the carrier coordinate system to the vehicle coordinate system; the rotation matrix is initialized to a third-order identity matrix, and a first-order Taylor expansion is performed on the Gauss-Newton iterative objective function to obtain the Jacobian matrix corresponding to the Gauss-Newton iterative objective function; The second unit is used to establish a linear least squares relationship based on the Jacobian matrix, and obtain a constraint equation including a Hessian matrix and a bias matrix by deriving the linear least squares relationship and setting the derivative to zero; iteratively performing the solution of the Jacobian matrix, the construction of the Hessian matrix and the bias matrix, and the update operation of the transformation matrix until the Gauss-Newton iterative objective function of the IMU installation angle estimation converges, and determining the transformation matrix obtained from the last iteration as the optimal rotation matrix; The third unit is used to calculate the optimal pitch installation angle and the optimal yaw installation angle through inverse trigonometric functions based on the matrix elements in the optimal rotation matrix, wherein the optimal pitch installation angle is obtained by the inverse sine function of the elements in the third row and first column of the optimal rotation matrix, and the optimal yaw installation angle is obtained by the inverse tangent function of the elements in the third row and second column and the elements in the third row and third column of the optimal rotation matrix.

[0038] According to a third aspect of the embodiments of the present invention, An electronic device is provided, comprising: processor; a memory for storing processor-executable instructions; The processor is configured to call the instructions stored in the memory to execute the aforementioned method.

[0039] According to a fourth aspect of the embodiments of the present invention, A computer-readable storage medium is provided, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the method described above is implemented.

[0040] The present invention may be a method, an apparatus, a system and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for executing various aspects of the present invention.

[0041] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A vehicle-mounted IMU installation angle estimation method based on Gauss-Newton iteration is characterized in that: include: Constructing a Gauss-Newton iterative objective function for IMU installation angle estimation, the Gauss-Newton iterative objective function includes the true three-dimensional position information obtained from the fixed solution of the satellite navigation equipment, the integrated three-dimensional position information of the strapdown inertial navigation, and the rotation matrix from the carrier coordinate system to the vehicle coordinate system; initializing the rotation matrix to a third-order identity matrix, and performing a first-order Taylor expansion on the Gauss-Newton iterative objective function to obtain the Jacobian matrix corresponding to the Gauss-Newton iterative objective function; A linear least squares relationship is established based on the Jacobian matrix, and a constraint equation including a Hessian matrix and a bias matrix is obtained by differentiating the linear least squares relationship and setting the derivative to zero; solving the Jacobian matrix, constructing the Hessian matrix and the bias matrix, and updating the transformation matrix are iteratively performed until the Gauss-Newton iterative objective function of the IMU installation angle estimation converges, and the transformation matrix obtained from the last iteration is determined as the optimal rotation matrix; According to the matrix elements in the optimal rotation matrix, the optimal pitch installation angle and the optimal yaw installation angle are calculated by inverse trigonometric functions, wherein the optimal pitch installation angle is obtained by the inverse sine function of the elements in the third row and first column of the optimal rotation matrix, and the optimal yaw installation angle is obtained by the inverse tangent function of the elements in the third row and second column and the elements in the third row and third column of the optimal rotation matrix.

2. The method according to claim 1, characterized in that The Gauss-Newton iterative objective function for constructing the IMU installation angle estimation includes: ； The Gauss-Newton iterative objective function for IMU installation angle estimation is used. By continuously adjusting the IMU installation angle to minimize the objective function, the accurate IMU installation angle can be obtained, and the estimation of the IMU installation angle can be completed. N is the number of points where the selected satellite navigation equipment is in a fixed solution state. is the real three-dimensional position information obtained from the i-th satellite fixed solution, To select the i-th satellite navigation fixed solution, the strapdown inertial navigation integrated three-dimensional position information is: is the rotation matrix from the carrier coordinate system to the vehicle coordinate system.

3. The method according to claim 2, characterized in that Initialize the rotation matrix to a third-order identity matrix, and perform a first-order Taylor expansion on the Gauss-Newton iterative objective function to obtain the Jacobian matrix corresponding to the Gauss-Newton iterative objective function, including: The perturbation model is used to perform Lie group and Lie algebra transformation on the rotation matrix. By multiplying the rotation matrix by a small amount on the left and solving the Lie algebraic change rate relative to the small amount, the rotation matrix is derivatized to obtain the specific expression of the Jacobian matrix: ； in, is the rotation matrix Multiply a small amount on the left The corresponding Lie algebra is, is the rotation center of the IMU coordinate system.

4. The method according to claim 1, wherein The Hessian matrix is the product of the Jacobian matrix and its transpose, and the bias matrix is the product of the Jacobian matrix and the objective function.

5. The method according to claim 1, wherein The method further comprises: Substituting the Hessian matrix and the bias matrix into the incremental equation of the Gauss-Newton method to obtain the increment of the conversion matrix; The increment of the conversion matrix is substituted into the conversion matrix update formula to obtain the updated conversion matrix.

6. The method according to claim 1, characterized in that Calculating the optimal pitch installation angle and the optimal yaw installation angle using inverse trigonometric functions based on the matrix elements in the optimal rotation matrix includes: Based on the optimal rotation matrix , convert to get the optimal pitch installation angle , and the optimal heading installation angle , its conversion expression is: ； For the optimal pitch installation angle, is the optimal heading installation angle, is the optimal rotation matrix The element in the first row and first column of is the optimal rotation matrix The element in the second row and first column of is the optimal rotation matrix The element in the third row and first column of is the optimal rotation matrix The element in the third row and second column of is the optimal rotation matrix The element in the third row and third column of .

7. A vehicle-mounted IMU installation angle estimation system based on Gauss-Newton iteration, used to implement the method according to any one of claims 1 to 6, characterized in that: include: The first unit is used to construct a Gauss-Newton iterative objective function for IMU installation angle estimation, wherein the Gauss-Newton iterative objective function includes the real three-dimensional position information obtained by the fixed solution of the satellite navigation equipment, the three-dimensional position information of the strapdown inertial navigation integration, and the rotation matrix from the carrier coordinate system to the vehicle coordinate system; the rotation matrix is initialized to a third-order identity matrix, and a first-order Taylor expansion is performed on the Gauss-Newton iterative objective function to obtain the Jacobian matrix corresponding to the Gauss-Newton iterative objective function; The second unit is used to establish a linear least squares relationship based on the Jacobian matrix, and obtain a constraint equation including a Hessian matrix and a bias matrix by deriving the linear least squares relationship and setting the derivative to zero; iteratively performing the solution of the Jacobian matrix, the construction of the Hessian matrix and the bias matrix, and the update operation of the transformation matrix until the Gauss-Newton iterative objective function of the IMU installation angle estimation converges, and determining the transformation matrix obtained from the last iteration as the optimal rotation matrix; The third unit is used to calculate the optimal pitch installation angle and the optimal yaw installation angle through inverse trigonometric functions based on the matrix elements in the optimal rotation matrix, wherein the optimal pitch installation angle is obtained by the inverse sine function of the elements in the third row and first column of the optimal rotation matrix, and the optimal yaw installation angle is obtained by the inverse tangent function of the elements in the third row and second column and the elements in the third row and third column of the optimal rotation matrix.

8. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to call the instructions stored in the memory to execute the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the computer program instructions are executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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