Vehicle-mounted IMU installation angle online estimation method and device

Abstract

The present application relates to a kind of vehicle-mounted IMU installation bias angle online estimation method and device, its method includes: obtaining the multiple sets of static pose data of vehicle-mounted IMU to be calibrated vehicle;The multiple sets of static pose data are preprocessed, and the preprocessing includes screening, mean calculation and normalization processing;Based on the multiple sets of static pose data after preprocessing, by coordinate transformation and the relative rotation between different static poses of vehicle, construct overdetermined equation group;By nonlinear least square method, the overdetermined equation group is solved, and the installation bias angle of the vehicle-mounted IMU to be calibrated is obtained.The present application is effectively inhibited noise interference by multi-pose constraint and least square estimation, and precision and robustness are far superior to traditional static method, cost is extremely low, and operation is simple.

Description

Technical Field

[0001] This invention belongs to the field of vehicle-assisted driving technology, specifically relating to an online estimation method and device for the installation angle of an on-board IMU, and more particularly to an online estimation method and device for the installation angle of an on-board IMU based on static multi-attitude constraints. Background Technology

[0002] With the rapid development of automotive intelligence and connectivity technologies, inertial measurement units (IMUs) have gradually evolved from being exclusive to high-end models to becoming one of the core sensors in intelligent driving systems (such as ADAS and autonomous driving) of many mainstream vehicles. IMUs can provide high-frequency vehicle motion information (three-axis angular velocity and acceleration) unaffected by external environmental interference, providing an irreplaceable data source for vehicle attitude estimation, dead reckoning, and stability control. However, the measurement accuracy of IMUs heavily relies on the precise alignment between their coordinate system and the vehicle coordinate system. Mechanical deviations during actual installation, i.e., installation offset angles, introduce systematic measurement errors. If not compensated for, this will directly lead to distortion in vehicle state estimation, affecting the performance of upper-level control algorithms and driving safety.

[0003] Existing vehicle-mounted IMU installation angle calibration technologies are mainly divided into two categories: high-precision dynamic calibration and low-cost static calibration. High-precision dynamic calibration typically relies on a GNSS / IMU integrated navigation system. It estimates the installation angle by fusing high-frequency IMU data and high-precision GNSS pose information as the vehicle travels along a specific path, and then using filtering algorithms. This method is highly accurate, but extremely expensive, requiring specialized equipment and facilities. It is limited to pre-installed R&D and high-end testing, and cannot be applied to mass-produced vehicles or aftermarket scenarios.

[0004] Low-cost static calibration utilizes a gravity field reference. The most basic method requires the vehicle to be parked on an absolutely level surface, and the pitch and roll installation angles are directly calculated through a single accelerometer measurement. This method heavily relies on the ideal assumption of "absolute level," which is difficult to achieve in reality. Actual site slope and vehicle tilt will introduce indistinguishable errors, leading to calibration failure.

[0005] Therefore, existing technologies suffer from a prominent contradiction between cost and accuracy, and between ideal assumptions and real-world conditions, lacking a practical calibration scheme that is both low-cost and highly robust. Summary of the Invention

[0006] To achieve low-cost static calibration of the mounting angle of an onboard IMU while maintaining high robustness, the first aspect of this invention provides an online estimation method for the mounting angle of an onboard IMU, comprising: acquiring multiple sets of static pose data of the vehicle where the onboard IMU to be calibrated is located; preprocessing the multiple sets of static pose data, the preprocessing including filtering, mean calculation and normalization; based on the preprocessed multiple sets of static pose data, constructing an overdetermined system of equations through coordinate transformation and relative rotation between different static poses of the vehicle; and solving the overdetermined system of equations using the nonlinear least squares method to obtain the mounting angle of the onboard IMU to be calibrated.

[0007] In some embodiments of the present invention, the construction of an overdetermined equation set based on multiple sets of preprocessed static pose data, through coordinate transformation and relative rotation between different static poses of the vehicle, includes: determining the vehicle coordinate system, the IMU coordinate system, and the navigation coordinate system; determining the coordinate transformation relationship from the IMU coordinate system to the vehicle coordinate system, and from the vehicle coordinate system to the navigation coordinate system; and constructing an overdetermined equation set based on the coordinate transformation relationship and the relative rotation between poses.

[0008] Furthermore, the construction of the overdetermined equation set through coordinate transformation and relative rotation between different static poses of the vehicle includes: using the relative rotation relationship between different static poses of the vehicle to eliminate the transformation from the vehicle coordinate system to the navigation coordinate system in the coordinate transformation relationship; and constructing the overdetermined equation set based on the coordinate transformation relationship obtained after elimination.

[0009] In some embodiments of the present invention, the step of solving the overdetermined system of equations using the nonlinear least squares method to obtain the installation angle of the vehicle-mounted IMU to be calibrated includes: converting the overdetermined system of equations into an objective function that minimizes the sum of squared residuals using the nonlinear least squares method; solving the objective function based on a numerical optimization algorithm to obtain an estimate of the optimal installation rotation matrix; and extracting the installation angle of the vehicle-mounted IMU to be calibrated based on the estimate of the optimal installation rotation matrix.

[0010] Furthermore, the step of solving the objective function based on the numerical optimization algorithm to obtain the estimated value of the optimal installation rotation matrix includes: solving the objective function using the Levenberg-Marquardt algorithm to obtain the estimated value of the optimal installation rotation matrix.

[0011] In the above embodiments, the method further includes: compensating for the vehicle's pose data based on the installation offset angle.

[0012] A second aspect of the present invention provides an online estimation device for the mounting angle of a vehicle-mounted IMU, comprising: an acquisition module for acquiring multiple sets of static pose data of the vehicle where the vehicle-mounted IMU to be calibrated is located; a preprocessing module for preprocessing the multiple sets of static pose data, the preprocessing including filtering, mean calculation and normalization; a construction module for constructing an overdetermined system of equations based on the preprocessed multiple sets of static pose data, through coordinate transformation and relative rotation between different static poses of the vehicle; and a solution module for solving the overdetermined system of equations using a nonlinear least squares method to obtain the mounting angle of the vehicle-mounted IMU to be calibrated.

[0013] Furthermore, the construction module includes: a first determining unit for determining the vehicle coordinate system, the IMU coordinate system, and the navigation coordinate system; a second determining unit for determining the coordinate transformation relationship from the IMU coordinate system to the vehicle coordinate system and from the vehicle coordinate system to the navigation coordinate system; and a construction unit for constructing an overdetermined set of equations based on the coordinate transformation relationship and the relative rotation between attitudes.

[0014] A third aspect of the present invention provides an electronic device comprising: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the online estimation method for the installation deflection angle of a vehicle-mounted IMU provided in the first aspect of the present invention.

[0015] In a fourth aspect, the present invention provides a computer-readable medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the online estimation method for the installation deflection angle of an on-board IMU provided in the first aspect of the present invention.

[0016] The beneficial effects of this invention are:

[0017] This invention completely eliminates the dependence on an absolutely level field, greatly enhancing its applicability; it employs multi-pose constraints and least squares estimation to effectively suppress noise interference, and its accuracy and robustness are far superior to traditional static methods; this invention requires no additional hardware throughout the process, has extremely low cost, is easy to operate, and has great potential for industrialization. Attached Figure Description

[0018] Figure 1 This is a basic flowchart illustrating the online estimation method for the installation angle of a vehicle-mounted IMU in some embodiments of the present invention;

[0019] Figure 2 This is a schematic diagram illustrating the specific process of the online estimation method for the installation angle of a vehicle-mounted IMU in some embodiments of the present invention;

[0020] Figure 3 This is a schematic diagram of the structure of the vehicle-mounted IMU installation deflection online estimation device in some embodiments of the present invention;

[0021] Figure 4 This is a schematic diagram of the structure of an electronic device in some embodiments of the present invention. Detailed Implementation

[0022] The principles and features of the present invention are described below with reference to the accompanying drawings. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0023] refer to Figure 1 and Figure 2 In a first aspect of the present invention, an online estimation method for the installation deflection angle of a vehicle-mounted IMU is provided, comprising: S100. acquiring multiple sets of static pose data of the vehicle where the vehicle-mounted IMU to be calibrated is located; S200. preprocessing the multiple sets of static pose data, wherein the preprocessing includes filtering, mean calculation and normalization; S300. constructing an overdetermined set of equations based on the preprocessed multiple sets of static pose data by coordinate transformation and relative rotation between different static poses of the vehicle; S400. solving the overdetermined set of equations by nonlinear least squares method to obtain the installation deflection angle of the vehicle-mounted IMU to be calibrated.

[0024] In step S100 of some embodiments of the present invention, multiple sets of static pose data of the vehicle where the vehicle-mounted IMU to be calibrated is located are obtained.

[0025] Specifically, vehicle preparation: Park the vehicle equipped with the IMU to be calibrated in a normal field. The field does not need to be perfectly level, but it should be as flat and stable as possible to avoid violent vibrations.

[0026] Attitude planning: Plan at least three static vehicle attitudes. Recommended attitudes are:

[0027] Attitude 1 (Initial Attitude): The vehicle is parked with its front facing straight ahead.

[0028] Posture 2 (Reverse Posture): Rotate the vehicle approximately 180° around its vertical axis so that the front of the vehicle is facing directly rearward. Ensure that the vehicle is parked in the same position as in Posture 1 to maintain a consistent ground tilt.

[0029] Posture 3 (Side Posture): Rotate the vehicle about 90° around its vertical axis so that the front of the vehicle is facing left or right.

[0030] Data recording: With the vehicle completely stationary (engine off, passengers off), data is collected sequentially from the IMU accelerometer output via the vehicle network (e.g., CAN bus) while maintaining each posture. Data is collected continuously for a period of time (e.g., 5-10 seconds) at each posture, with the sampling frequency determined based on IMU performance (typically 100Hz).

[0031] Only after the recording is complete can the next posture change be performed.

[0032] In step S200 of some embodiments of the present invention, the multiple sets of static pose data are preprocessed, and the preprocessing includes filtering, mean calculation and normalization.

[0033] Specifically, data filtering: The raw data collected under each posture is filtered to remove abnormal data points caused by slight shaking or impact, ensuring that all data are obtained when the vehicle is stationary.

[0034] Mean Calculation: For each selected stable data segment under each attitude, calculate the average value of the triaxial acceleration measurements `(a_x^k, a_y^k, a_z^k)`, where `k=1,2,3^ represents the attitude number. This average value is the best estimate of the gravitational acceleration vector in the IMU coordinate system under that attitude.

[0035] Normalization: To simplify the calculation, the above average vector is normalized (i.e., divided by the magnitude of the local gravitational acceleration g) to obtain the unit gravity vector G_i^k = [a_x^k, a_y^k, a_z^k]^T / g.

[0036] In step S300 of some embodiments of the present invention, the construction of an overdetermined equation set based on preprocessed multiple sets of static pose data, through coordinate transformation and relative rotation between different static poses of the vehicle, includes:

[0037] S301. Determine the vehicle coordinate system, IMU coordinate system, and navigation coordinate system;

[0038] Specifically, define the vehicle coordinate system (V-system): the X-axis points directly forward of the vehicle, the Y-axis points to the driver's left, and the Z-axis points upward, forming a right-handed coordinate system. Define the IMU coordinate system (I-system): fixedly connected to the IMU sensor. Define the navigation coordinate system (N-system): a northeast-sky coordinate system.

[0039] S302. Determine the coordinate transformation relationship from the IMU coordinate system to the vehicle coordinate system, and from the vehicle coordinate system to the navigation coordinate system;

[0040] Specifically, according to the principle of coordinate transformation, for each pose k, the following relationship exists:

[0041] G_i^k=(R_i^v)^T*(R_v^n_k)^T*[0, 0, 1]^T

[0042] Where: R_i^v is the installation rotation matrix from the IMU coordinate system to the vehicle coordinate system (to be determined); R_v^n_k is the rotation matrix from the vehicle coordinate system to the navigation coordinate system (including unknown ground tilt and known vehicle steering).

[0043] S303. Based on the coordinate transformation relationship and the relative rotation between attitudes, construct an overdetermined set of equations.

[0044] Furthermore, the construction of the overdetermined equation set through coordinate transformation and relative rotation between different static poses of the vehicle includes: using the relative rotation relationship between different static poses of the vehicle to eliminate the transformation from the vehicle coordinate system to the navigation coordinate system in the coordinate transformation relationship; and constructing the overdetermined equation set based on the coordinate transformation relationship obtained after elimination.

[0045] Specifically, using the known steering angles between vehicle attitudes (e.g., 180° and 90°), the unknown absolute attitude R_v^n_k is eliminated. The relative rotation matrix R_v^v_k1 of attitude k relative to attitude 1 is known (e.g., 180° steering: diag([-1, -1, 1])). The core equation is derived as follows:

[0046] R_i^v*G_i^k=(R_v^v_k1)^T*(R_i^v*G_i^1);

[0047] Let h = R_i^v * G_i^1, then the equation simplifies to:

[0048] R_i^v*G_i^k-(R_v^v_k1)^T*h=0 (for k=2,3,...);

[0049] Finally, a system of equations is constructed: by combining the equations for k=2 and k=3 with the equation for k=1 (R_i^v * G_i^1 - h = 0), an overdetermined system of equations is obtained with respect to the unknowns R_i^v (which contains 2 degrees of freedom) and h (which contains 2 degrees of freedom).

[0050] In step S400 of some embodiments of the present invention, the step of solving the overdetermined system of equations using the nonlinear least squares method to obtain the installation angle of the vehicle-mounted IMU to be calibrated includes:

[0051] S401. The overdetermined system of equations is transformed into an objective function that minimizes the sum of squared residuals using the nonlinear least squares method;

[0052] Specifically, the above system of equations is transformed into a nonlinear least squares optimization problem. The objective function is to minimize the sum of squared residuals on both sides of all equations.

[0053] S402. Based on the numerical optimization algorithm, solve the objective function to obtain the estimated value of the optimal installation rotation matrix;

[0054] Furthermore, the step of solving the objective function based on the numerical optimization algorithm to obtain the estimated value of the optimal installation rotation matrix includes: solving the objective function using the Levenberg-Marquardt algorithm to obtain the estimated value of the optimal installation rotation matrix R_i^v.

[0055] It is understandable that numerical optimization algorithms also include the Gauss-Newton method, the steepest descent method, the conjugate gradient method, the dogleg method, and algorithms based on stochastic gradient descent.

[0056] S403. Based on the estimated value of the optimal installation rotation matrix, extract the installation angle of the vehicle-mounted IMU to be calibrated.

[0057] Specifically, from the obtained rotation matrix 'R_i^v', the installation roll angle φ_install and installation pitch angle θ_install are extracted according to the following formulas:

[0058] θ_install=arcsin(R_i^v(1,3));

[0059] φ_install=-arctan2(R_i^v(2,3),R_i^v(3,3)).

[0060] In the above embodiments, the method further includes: compensating for the vehicle's pose data based on the installation offset angle.

[0061] Specifically, the results are verified as follows: The solved installation deflection angle is substituted into the observation equation to calculate the theoretical gravity projection, and then compared with the actual measured value to verify the reliability of the calibration results. Parameter storage: The calibrated installation deflection angle parameters are written into the non-volatile memory of the vehicle's electronic control unit (ECU). Online compensation: During actual vehicle operation, the ECU calls the stored installation deflection angle parameters to perform real-time coordinate rotation compensation on the raw acceleration and angular velocity data read by the IMU, transforming it to a standard vehicle coordinate system for use by the upper-level control system.

[0062] Example 2

[0063] refer to Figure 3 In a second aspect, the present invention provides an online estimation device 1 for the mounting angle of a vehicle-mounted IMU, comprising: an acquisition module 11 for acquiring multiple sets of static pose data of the vehicle where the vehicle-mounted IMU to be calibrated is located; a preprocessing module 12 for preprocessing the multiple sets of static pose data, the preprocessing including filtering, mean calculation and normalization; a construction module 13 for constructing an overdetermined set of equations based on the preprocessed multiple sets of static pose data, through coordinate transformation and relative rotation between different static poses of the vehicle; and a solution module 14 for solving the overdetermined set of equations using a nonlinear least squares method to obtain the mounting angle of the vehicle-mounted IMU to be calibrated.

[0064] Furthermore, the construction module 13 includes: a first determining unit for determining the vehicle coordinate system, the IMU coordinate system, and the navigation coordinate system; a second determining unit for determining the coordinate transformation relationship from the IMU coordinate system to the vehicle coordinate system and from the vehicle coordinate system to the navigation coordinate system; and a construction unit for constructing an overdetermined set of equations based on the coordinate transformation relationship and the relative rotation between attitudes.

[0065] Example 3

[0066] refer to Figure 4 A third aspect of the present invention provides an electronic device comprising: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the online estimation method for the installation angle of an on-board IMU according to the first aspect of the present invention.

[0067] Electronic device 500 may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 501, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 502 or a program loaded from storage device 508 into random access memory (RAM) 503. The RAM 503 also stores various programs and data required for the operation of electronic device 500. The processing unit 501, ROM 502, and RAM 503 are interconnected via bus 504. An input / output (I / O) interface 505 is also connected to bus 504.

[0068] Typically, the following devices can be connected to I / O interface 505: input devices 506 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 507 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 508 including, for example, hard disks; and communication devices 509. Communication device 509 allows electronic device 500 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 4 An electronic device 500 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 4 Each box shown can represent a device or multiple devices as needed.

[0069] Specifically, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 509, or installed from a storage device 508, or installed from a ROM 502. When the computer program is executed by a processing device 501, it performs the functions defined in the methods of embodiments of this disclosure. It should be noted that the computer-readable medium described in embodiments of this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In embodiments of this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In embodiments of this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0070] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more computer programs, which, when executed by the electronic device, cause the electronic device to:

[0071] Computer program code for performing the operations of embodiments of this disclosure can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages—such as Java, Smalltalk, C++, and Python—and conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0072] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0073] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for online estimation of the installation deflection angle of a vehicle-mounted IMU, characterized in that, include: Acquire multiple sets of static pose data of the vehicle where the on-board IMU to be calibrated is located; The multiple sets of static pose data are preprocessed, including filtering, mean calculation and normalization. Based on multiple sets of preprocessed static pose data, an overdetermined set of equations is constructed through coordinate transformation and relative rotation between different static poses of the vehicle. The overdetermined equation set, constructed based on preprocessed multiple sets of static pose data and through coordinate transformation and relative rotation between different static poses of the vehicle, includes: Determine the vehicle coordinate system, IMU coordinate system, and navigation coordinate system; Determine the coordinate transformation relationship from the IMU coordinate system to the vehicle coordinate system, and from the vehicle coordinate system to the navigation coordinate system; Based on the coordinate transformation relationship and the relative rotation between attitudes, an overdetermined system of equations is constructed; By utilizing the relative rotation relationship between different static poses of the vehicle, the transformation from the vehicle coordinate system to the navigation coordinate system is eliminated in the coordinate transformation relationship; The overdetermined system of equations is constructed based on the coordinate transformation relationship obtained after elimination. The installation angle of the vehicle-mounted IMU to be calibrated is obtained by solving the overdetermined system of equations using the nonlinear least squares method.

2. The online estimation method for the installation angle of a vehicle-mounted IMU according to claim 1, characterized in that, The method of solving the overdetermined system of equations using nonlinear least squares to obtain the installation angle of the vehicle-mounted IMU to be calibrated includes: The overdetermined system of equations is transformed into an objective function that minimizes the sum of squared residuals using the nonlinear least squares method. Based on the numerical optimization algorithm, the objective function is solved to obtain an estimate of the optimal installation rotation matrix; Based on the estimated value of the optimal installation rotation matrix, the installation offset angle of the vehicle-mounted IMU to be calibrated is extracted.

3. The online estimation method for the installation deflection angle of the vehicle-mounted IMU according to claim 2, characterized in that, The process of solving the objective function using a numerical optimization algorithm to obtain an estimate of the optimal installation rotation matrix includes: The objective function is solved using the Levenberg-Marquardt algorithm to obtain an estimate of the optimal installation rotation matrix.

4. The online estimation method for the installation deflection angle of a vehicle-mounted IMU according to claim 1, characterized in that, Also includes: Based on the aforementioned installation offset angle, the vehicle's pose data is compensated.

5. A vehicle-mounted IMU installation angle online estimation device applying the online estimation method for vehicle-mounted IMU installation angle as described in any one of claims 1-4, characterized in that, include: The acquisition module is used to acquire multiple sets of static pose data of the vehicle where the on-board IMU to be calibrated is located; The preprocessing module is used to preprocess the multiple sets of static pose data. The preprocessing includes filtering, mean calculation and normalization. The module is used to construct an overdetermined set of equations based on multiple sets of preprocessed static pose data, through coordinate transformation and relative rotation between different static poses of the vehicle. The solution module is used to solve the overdetermined system of equations using the nonlinear least squares method to obtain the installation angle of the vehicle-mounted IMU to be calibrated.

6. The vehicle-mounted IMU installation angle online estimation device according to claim 5, characterized in that, The building module includes: The first determining unit is used to determine the vehicle coordinate system, the IMU coordinate system, and the navigation coordinate system; The second determining unit is used to determine the coordinate transformation relationship from the IMU coordinate system to the vehicle coordinate system, and from the vehicle coordinate system to the navigation coordinate system; The construction unit is used to construct an overdetermined system of equations based on the coordinate transformation relationship and the relative rotation between the attitudes.

7. An electronic device, comprising: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the online estimation method for the installation deflection angle of an on-board IMU as described in any one of claims 1 to 4.

8. A computer-readable medium having a computer program stored thereon, wherein, When the computer program is executed by the processor, it implements the online estimation method for the installation angle of the vehicle-mounted IMU as described in any one of claims 1 to 4.

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