Multi-gyroscope redundant resonator gyro inertial navigation drift online estimation method, system and device

Abstract

The present application relates to the technical field of gyro drift estimation, and particularly relates to a multi-gyro redundant resonator gyro inertial navigation drift online estimation method, system and device. The method comprises the following steps: monitoring the gyro state, obtaining the output of the remaining gyro according to the input of any gyro; setting the gyro inertial unit providing input to a pure full angle mode, which is used to provide the output of other gyro; controlling the estimated gyro inertial unit to stay at different array angles, and performing drift estimation on the estimated gyro inertial unit; setting the gyro inertial unit whose drift estimation is completed to a pure full angle mode until the drift estimation of all gyro inertial units is completed. The present application proposes a drift estimation method of hemispherical resonator gyro based on a multi-gyro redundant architecture, and improves the output precision of gyro.

Description

Technical Field

[0001] This invention relates to the field of gyroscope drift estimation technology, and in particular to an online method, system, and device for estimating drift of a multi-gyroscope redundant resonant gyroscope inertial navigation system. Background Technology

[0002] In existing technologies, due to limitations in current manufacturing processes, micro-cracks can develop on the lip, hemispherical shell surface, and support rod of the resonator. When the resonator vibrates, the size and distribution of these cracks may change, affecting the gyroscope's lifespan. These cracks also affect the resonator's stiffness and leave residual internal stress; the uneven distribution of cracks leads to uneven distribution of residual internal stress, resulting in inconsistent stiffness and damping at different locations within the resonator. Summary of the Invention

[0003] This invention aims to at least solve one of the technical problems existing in related technologies. To this end, this invention provides a method, system, and apparatus for online estimation of drift in a multi-gyroscope redundant resonant gyroscope inertial navigation system, thereby improving the accuracy of gyroscope output.

[0004] This invention provides an online estimation method for drift of a multi-gyroscope redundant resonant gyroscope inertial navigation system, comprising the following steps:

[0005] S1: Divide the gyroscope inertial group into two inertial groups, inertial group A and inertial group B, monitor the gyroscope state, and set the gyroscope inertial group that provides the input to pure full-angle mode to provide the output of the estimated gyroscope inertial group;

[0006] S2: Control the estimated gyroscope inertial navigation system to stay at different array angles, and perform drift estimation on the estimated gyroscope inertial navigation system;

[0007] S3: Set the estimated gyro inertial group to pure full-angle mode as the gyro inertial group to provide input, return to step S2, estimate another gyro inertial group, and complete the drift estimation.

[0008] According to the present invention, a method for online estimation of drift of a multi-gyroscope redundant resonant gyroscope inertial navigation system is provided, wherein step S1 includes:

[0009] S11: Calculate the estimated angular velocity of the carrier for all gyro inertial navigation systems using least squares estimation;

[0010] S12: Project all gyroscope inertial navigation systems onto a fixed orthogonal coordinate system and calculate the transformation matrix between the inertial navigation systems;

[0011] S13: Obtain the estimated angular velocity of one gyroscope inertial navigation system, input the estimated value into the transformation matrix to calculate the output representation of the remaining gyroscopes.

[0012] According to the present invention, a method for online estimation of drift of a multi-gyroscope redundant resonant gyroscope inertial navigation system is provided, wherein step S11 includes the following steps:

[0013] S111: For an inertial navigation system using n single-degree-of-freedom gyroscopes, the measurement input of the gyroscopes is expressed by the following formula:

[0014]

[0015] in, For measurement vectors; To configure the matrix; The angular velocity of the carrier; This is the gyroscope drift vector;

[0016] S112: Based on the least squares estimation theory, the estimated value of the carrier's angular velocity is obtained. :

[0017]

[0018] in, For matrix transpose, This is the characteristic matrix.

[0019] According to the present invention, a method for online estimation of drift of a multi-gyroscope redundant resonant gyroscope inertial navigation system is provided, wherein step S12 includes the following steps:

[0020] Divide all gyroscope inertial groups into two inertial groups and project them onto a fixed orthogonal coordinate system. Calculate the transformation matrix between the inertial groups and the orthogonal coordinate system B:

[0021]

[0022]

[0023]

[0024] in, This outputs the angular velocity in the x-direction of an orthogonal coordinate system. This outputs the angular velocity in the y-direction of an orthogonal coordinate system. Angular velocity output in the z-direction of an orthogonal coordinate system. Let be the transformation matrix from inertial navigation system A to system B. This refers to the gyroscope output in the x-direction of inertial navigation system A. This refers to the gyroscope output in the y-direction of inertial navigation system A. This refers to the gyroscope output in the z-direction of inertial navigation system A. This refers to the gyro drift in the x-direction of inertial navigation system A. This represents the gyro drift in the y-direction of inertial navigation system A. This refers to the gyro drift in the z-direction of inertial navigation system A. Let be the transformation matrix from inertial navigation system B to system B. This refers to the gyroscope output in the x-direction of inertial navigation system B. This refers to the gyroscope output in the y-direction of inertial navigation system B. This refers to the gyroscope output in the z-direction of inertial navigation system B. This refers to the gyro drift in the x-direction within inertial navigation system B. This represents the gyro drift in the y-direction of inertial navigation system B. This refers to the gyro drift in the z-direction within inertial navigation system B.

[0025] Since the non-orthogonal error angle of the gyroscope within one inertial navigation system and the non-parallelism error angle between two inertial navigation systems are less than 1°, the formula can be rewritten as:

[0026] .

[0027] According to the present invention, a method for online estimation of drift of a multi-gyroscope redundant resonant gyroscope inertial navigation system is provided, wherein step S2 includes:

[0028] S21: When estimating the drift of inertial group A, control inertial group B to be in pure full-angle mode. The mode shape precession of the gyroscope of inertial group A to different mode shape angles will induce drift changes.

[0029] S22: Determine the number of low-order drift terms based on the drift changes, and select the corresponding formation angle based on the number of low-order drift terms;

[0030] S23: By controlling the mode shape, the mode shape of gyroscope A is controlled to stay at different mode shape angles, while gyroscope B is always in full-angle mode. The drift value of gyroscope A is estimated online using the drift estimation method.

[0031] According to the present invention, a method for online estimation of drift of a multi-gyroscope redundant resonant gyroscope inertial navigation system is provided. Step S22 includes the following steps: the number of low-order drift terms includes 1 zero-order term, 2 first-order terms, and 2 second-order terms, with corresponding array angles of 0°, 18°, 36°, 52°, and 72°.

[0032] According to the present invention, an online drift estimation method for a multi-gyroscope redundant resonant gyroscope inertial navigation system is provided, wherein the drift estimation method includes the least squares method and the Kalman filter method.

[0033] This invention also provides an online drift estimation system for multi-gyroscope redundant resonant gyroscope inertial navigation, comprising:

[0034] Gyroscope output representation acquisition module: Divides the gyroscope inertial group into two inertial groups, inertial group A and inertial group B, monitors the gyroscope state, sets the input gyroscope inertial group to pure full-angle mode, and provides the output of the estimated gyroscope inertial group;

[0035] Drift estimation module: controls the estimated gyroscope inertial group to stay at different array angles, and performs drift estimation on the estimated gyroscope inertial group;

[0036] Rotation estimation module: Set the estimated gyro inertial group to pure full-angle mode, use it as the input gyro inertial group, return to the drift estimation module, estimate another gyro inertial group, and complete the drift estimation.

[0037] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the online estimation method for drift of a multi-gyroscope redundant resonant gyroscope inertial navigation as described above.

[0038] The above-described one or more technical solutions in the embodiments of the present invention have at least one of the following technical effects:

[0039] This invention provides an online drift estimation method for multi-gyroscope redundant resonant gyroscopes and inertial navigation systems. Based on a multi-gyroscope redundancy architecture, a drift estimation method for hemispherical resonant gyroscopes is proposed, achieving the following advantages:

[0040] 1. The core advantage of this solution is that it enables online estimation and real-time compensation of gyroscope drift, directly solving the drift problem caused by uneven damping or stiffness of hemispherical resonant gyroscopes due to process defects such as cracks, and significantly improving the output accuracy of the inertial measurement unit (INS).

[0041] 2. To address the limitations of HRG manufacturing processes, which lead to drift that varies with the position of the standing wave, this solution uses a multi-gyroscope redundant architecture for mutual monitoring and drift estimation to offset the performance degradation caused by this inherent defect. This allows the long lifespan advantage of HRG to be fully utilized and avoids a decrease in system accuracy due to drift accumulation.

[0042] 3. This solution specifically corrects five low-order drift parameters, making the estimation more targeted and the correction effect better. It selects a low-dynamic environment for drift estimation, which effectively reduces the impact of non-target errors such as scaling error and installation error on the drift estimation results. At the same time, this solution does not limit the drift estimation method and can select high-precision algorithms such as least squares and Kalman filtering according to the actual scenario to adapt to different accuracy requirements.

[0043] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0045] Figure 1 This is a flowchart illustrating an online estimation method for drift of a multi-gyroscope redundant resonant gyroscope inertial navigation system provided by the present invention.

[0046] Figure 2 It consists of two sets of parallel, three-orthogonal six-gyroscope architectures.

[0047] Figure 3 Configure the architecture for two sets of parallel quad gyroscopes.

[0048] Figure 4 This is a schematic diagram of the drift process results.

[0049] Figure 5 This is a block diagram of an online drift estimation system for multi-gyroscope redundant resonant gyroscope inertial navigation provided by the present invention.

[0050] Figure 6 This is a schematic diagram of the electronic device provided by the present invention.

[0051] Figure label:

[0052] 810, Processor; 820, Communication interface; 830, Memory; 840, Communication bus. Detailed Implementation

[0053] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention. The following embodiments are used to illustrate this invention but cannot be used to limit the scope of this invention.

[0054] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0055] The following is combined Figures 1 to 6 This invention is described.

[0056] Example

[0057] Due to limitations in current manufacturing processes, micro-cracks may develop on the lip, hemispherical shell surface, and support rod of the resonator. When the resonator vibrates, the size and distribution of these cracks may change, affecting the gyroscope's lifespan. These cracks also affect the resonator's stiffness and leave residual internal stress; uneven crack distribution leads to uneven residual internal stress distribution, resulting in inconsistent stiffness and damping at different locations within the resonator. Multi-gyroscope redundancy structures include, but are not limited to, two sets of parallel tri-orthogonal six-gyroscope architectures and four-gyroscope configurations. The two sets of parallel tri-orthogonal six-gyroscope architectures are as follows: Figure 2 As shown. The four gyroscopes are configured as follows. Figure 3 (a) and Figure 3 As shown in (b).

[0058] Inconsistent damping at different positions in a hemispherical resonant gyroscope can cause the gyroscope to exhibit behavior that varies with the position of the standing wave. The changing drift, which can be represented by a Fourier series. Expand, represented as

[0059]

[0060] Indicates drift The magnitude of the item, Indicates drift The magnitude of the item, This refers to the number of expansions. Generally speaking... The larger the value, the smaller the coefficient of this term. For every 1 increase, the coefficient of this term decreases by an order of magnitude. Therefore, the drift is mainly affected by the lower-order terms of the Fourier series expansion. In general, it is mainly affected by the first and second order drifts. n is the number of degrees of freedom of the gyroscope.

[0061] like Figure 1 As shown, this invention proposes an online estimation method for drift of a multi-gyroscope redundant resonant gyroscope inertial navigation system, comprising the following steps:

[0062] S1: Divide the gyroscope inertial group into two inertial groups, inertial group A and inertial group B, monitor the gyroscope state, and set the gyroscope inertial group that provides the input to pure full-angle mode to provide the output of the estimated gyroscope inertial group;

[0063] S2: Control the estimated gyroscope inertial navigation system to stay at different array angles, and perform drift estimation on the estimated gyroscope inertial navigation system;

[0064] S3: Set the estimated gyro inertial group to pure full-angle mode as the gyro inertial group to provide input, return to step S2, estimate another gyro inertial group, and complete the drift estimation.

[0065] by Figure 2 Taking the six-gyroscope architecture shown as an example, inertial navigation systems A and B are usually calibrated in advance.

[0066] Specifically, step S1 includes:

[0067] S11: Calculate the estimated angular velocity of the carrier for all gyro inertial navigation systems using least squares estimation;

[0068] S12: Project all gyroscope inertial navigation systems onto a fixed orthogonal coordinate system and calculate the transformation matrix between the inertial navigation systems;

[0069] S13: Obtain the estimated angular velocity of one gyroscope inertial navigation system, input the estimated value into the transformation matrix to calculate the output representation of the remaining gyroscopes.

[0070] Specifically, step S11 includes the following steps:

[0071] S111: For an inertial navigation system using n single-degree-of-freedom gyroscopes, the measurement input of the gyroscopes can be expressed by the following formula:

[0072]

[0073] in, For measurement vectors; To configure the matrix; The angular velocity of the carrier; This is the gyroscope drift vector;

[0074] S112: According to the least squares estimation theory, the angular velocity of the carrier can be obtained. The estimated value :

[0075]

[0076] in, For matrix transpose, This is the characteristic matrix.

[0077] Specifically, step S12 includes the following steps:

[0078] Projecting all gyroscope inertial navigation systems (INS) onto a fixed orthogonal coordinate system B, the transformation matrix between the INS and the orthogonal coordinate system B is calculated:

[0079]

[0080]

[0081]

[0082] in, This outputs the angular velocity in the x-direction of an orthogonal coordinate system. This outputs the angular velocity in the y-direction of an orthogonal coordinate system. Angular velocity output in the z-direction of an orthogonal coordinate system. Let be the transformation matrix from inertial navigation system A to system B. This refers to the gyroscope output in the x-direction of inertial navigation system A. This refers to the gyroscope output in the y-direction of inertial navigation system A. This refers to the gyroscope output in the z-direction of inertial navigation system A. This refers to the gyro drift in the x-direction of inertial navigation system A. This represents the gyro drift in the y-direction of inertial navigation system A. This refers to the gyro drift in the z-direction of inertial navigation system A. Let be the transformation matrix from inertial navigation system B to system B. This refers to the gyroscope output in the x-direction of inertial navigation system B. This refers to the gyroscope output in the y-direction of inertial navigation system B. This refers to the gyroscope output in the z-direction of inertial navigation system B. This refers to the gyro drift in the x-direction of inertial navigation system B. This represents the gyro drift in the y-direction of inertial navigation system B. This refers to the gyro drift in the z-direction within inertial navigation system B.

[0083] Since the non-orthogonal error angle of a gyroscope within a single inertial navigation system and the non-parallelism error angle between two inertial navigation systems are less than 1°, the formula can be rewritten as:

[0084] .

[0085] Taking inertial group B monitoring inertial group A as an example, by rearranging the terms of the equation, the gyroscope monitoring error can be expressed as:

[0086]

[0087] All quantities on the right side of the equation are known quantities. Estimating the gyroscope monitoring error means estimating the gyroscope drift.

[0088] During drift estimation, inertial navigation systems (INS) A and INS B can serve as mutual references to ensure continuous INS output. While INS A performs drift estimation, INS B provides the angular velocity output of the INS.

[0089] To minimize the impact of other system errors (such as scaling and installation errors) on drift estimation, drift estimation must be performed in a low-dynamic environment. Drift estimation is performed in two steps: first, the drift of inertial group A is estimated, and second, the drift of inertial group B is estimated.

[0090] Specifically, step S2 includes:

[0091] S21: When estimating the drift of inertial group A, control inertial group B to be in pure full-angle mode. The mode shape precession of the gyroscope of inertial group A to different mode shape angles will induce drift changes.

[0092] S22: Determine the number of low-order drift terms based on the drift changes, and select the corresponding formation angle based on the number of low-order drift terms;

[0093] S23: By controlling the mode shape, the gyroscope of inertial group A is controlled to remain at different mode shape angles, while the gyroscope of inertial group B is always in full-angle mode. The drift value of inertial group A is estimated online using drift estimation methods. The drift estimation methods include the least squares method and the Kalman filter method.

[0094] Specifically, such as Figure 4 As shown, inertial navigation systems (INS) A and B alternately perform drift estimation, and after completing the estimation, they perform drift compensation. Then, the two INS systems jointly provide INS output angular velocity information. Before time T1, INS A performs drift estimation, while INS B is in full-angle mode and provides INS output. The opposite occurs between time T1 and T2. Between time T2 and T3, both INS systems complete the correction and provide normal output.

[0095] like Figure 5 As shown below, an online drift estimation system for multi-gyroscope redundant resonant gyroscope inertial navigation provided by the present invention will be described. The online drift estimation system for multi-gyroscope redundant resonant gyroscope inertial navigation described below can be referred to in correspondence with the online drift estimation method for multi-gyroscope redundant resonant gyroscope inertial navigation described above.

[0096] Gyroscope output representation acquisition module: Divides the gyroscope inertial group into two inertial groups, inertial group A and inertial group B, monitors the gyroscope state, sets the input gyroscope inertial group to pure full-angle mode, and provides the output of the estimated gyroscope inertial group;

[0097] Drift estimation module: controls the estimated gyroscope inertial group to stay at different array angles, and performs drift estimation on the estimated gyroscope inertial group;

[0098] Rotation estimation module: Set the estimated gyro inertial group to pure full-angle mode, use it as the input gyro inertial group, return to the drift estimation module, estimate another gyro inertial group, and complete the drift estimation.

[0099] Figure 6 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 6 As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830, and a communication bus 840, wherein the processor 810, the communication interface 820, and the memory 830 communicate with each other via the communication bus 840. The processor 810 can call logic instructions in the memory 830 to execute an online estimation method for drift of a multi-gyroscope redundant resonant gyroscope inertial navigation system, the method including:

[0100] S1: Divide the gyroscope inertial group into two inertial groups, inertial group A and inertial group B, monitor the gyroscope state, and set the gyroscope inertial group that provides the input to pure full-angle mode to provide the output of the estimated gyroscope inertial group;

[0101] S2: Control the estimated gyroscope inertial navigation system to stay at different array angles, and perform drift estimation on the estimated gyroscope inertial navigation system;

[0102] S3: Set the estimated gyro inertial group to pure full-angle mode as the gyro inertial group to provide input, return to step S2, estimate another gyro inertial group, and complete the drift estimation.

[0103] Furthermore, the logical instructions in the aforementioned memory 830 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0104] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0105] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0106] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

[0107] It should be noted that the embodiments of this disclosure can be implemented using hardware, software, or a combination of both. The hardware portion can be implemented using dedicated logic; the software portion can be stored in memory and executed by a suitable instruction execution system, such as a microprocessor or dedicated-design hardware. Those skilled in the art will understand that the above-described apparatus and methods can be implemented using computer-executable instructions and / or included in processor control code, for example, such code provided on a programmable memory or a data carrier such as an optical or electronic signal carrier.

[0108] Furthermore, although the operation of the methods of this disclosure is described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Rather, the steps depicted in the flowcharts may be performed in a different order. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps. It should also be noted that the features and functions of two or more devices according to this disclosure may be embodied in one device. Conversely, the features and functions of one device described above may be further divided and embodied by multiple devices.

[0109] While this disclosure has been described with reference to several specific embodiments, it should be understood that this disclosure is not limited to the specific embodiments disclosed. This disclosure is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Claims

1. A method for online estimation of drift in a multi-gyroscope redundant resonant gyroscope inertial navigation system, characterized in that, Includes the following steps: S1: Divide the gyroscope inertial group into two inertial groups, inertial group A and inertial group B, monitor the gyroscope state, and set the gyroscope inertial group that provides the input to pure full-angle mode to provide the output of the estimated gyroscope inertial group; S2: Control the estimated gyroscope inertial navigation system to remain at different array angles, and perform drift estimation on the estimated gyroscope inertial navigation system; Step S2 includes: S21: When estimating the drift of inertial group A, control inertial group B to be in pure full-angle mode. The mode shape precession of the gyroscope of inertial group A to different mode shape angles will induce drift changes. S22: Determine the number of low-order drift terms based on the drift changes, and select the corresponding formation angle based on the number of low-order drift terms; S23: By controlling the mode shape, the mode shape of gyroscope A is controlled to stay at different mode shape angles, while gyroscope B is always in full-angle mode. The drift value of gyroscope A is estimated online using the drift estimation method. S3: Set the estimated gyro inertial group to pure full-angle mode as the gyro inertial group to provide input, return to step S2, estimate another gyro inertial group, and complete the drift estimation.

2. The online estimation method for drift of a multi-gyroscope redundant resonant gyroscope inertial navigation system according to claim 1, characterized in that, Step S1 includes: S11: Calculate the estimated angular velocity of the carrier for all gyro inertial navigation systems using least squares estimation; S12: Project all gyroscope inertial navigation systems onto a fixed orthogonal coordinate system and calculate the transformation matrix between the inertial navigation systems; S13: Obtain the estimated angular velocity of one gyroscope inertial navigation system, input the estimated value into the transformation matrix to calculate the output representation of the remaining gyroscopes.

3. The online estimation method for drift of a multi-gyroscope redundant resonant gyroscope inertial navigation system according to claim 2, characterized in that, Step S11 includes the following steps: S111: For an inertial navigation system using n single-degree-of-freedom gyroscopes, the measurement input of the gyroscopes is expressed by the following formula: in, For measurement vectors; To configure the matrix; The angular velocity of the carrier; This is the gyroscope drift vector; S112: Based on the least squares estimation theory, the estimated value of the carrier's angular velocity is obtained. : in, For matrix transpose, This is the characteristic matrix.

4. The online estimation method for drift of a multi-gyroscope redundant resonant gyroscope inertial navigation system according to claim 3, characterized in that, Step S12 includes the following steps: The gyroscope inertial group is divided into two inertial groups and projected onto a fixed orthogonal coordinate system. The transformation matrix between the inertial groups and the orthogonal coordinate system is calculated. in, Outputs the angular velocity in the x-direction of an orthogonal coordinate system. This outputs the angular velocity in the y-direction of an orthogonal coordinate system. Angular velocity output in the z-direction of an orthogonal coordinate system. Let be the transformation matrix from inertial navigation system A to system B. This refers to the gyroscope output in the x-direction of inertial navigation system A. This refers to the gyroscope output in the y-direction of inertial navigation system A. This refers to the gyroscope output in the z-direction of inertial navigation system A. This refers to the gyro drift in the x-direction of inertial navigation system A. This represents the gyro drift in the y-direction of inertial navigation system A. This refers to the gyro drift in the z-direction of inertial navigation system A. Let be the transformation matrix from inertial navigation system B to system B. This refers to the gyroscope output in the x-direction of inertial navigation system B. This refers to the gyroscope output in the y-direction of inertial navigation system B. This refers to the gyroscope output in the z-direction of inertial navigation system B. This refers to the gyro drift in the x-direction of inertial navigation system B. This represents the gyro drift in the y-direction of inertial navigation system B. This refers to the gyro drift in the z-direction within inertial navigation system B. Since the non-orthogonal error angle of the gyroscope within one inertial navigation system and the non-parallelism error angle between two inertial navigation systems are less than 1°, the formula can be rewritten as: 。 5. The online estimation method for drift of a multi-gyroscope redundant resonant gyroscope inertial navigation system according to claim 1, characterized in that, Step S22 includes the following steps: the number of low-order drift terms includes 1 zero-order term, 2 first-order terms, and 2 second-order terms, with corresponding array angles of 0°, 18°, 36°, 52°, and 72°.

6. The online estimation method for drift of a multi-gyroscope redundant resonant gyroscope inertial navigation system according to claim 5, characterized in that, The drift estimation methods include least squares and Kalman filtering.

7. A multi-gyroscope redundant resonant gyroscope inertial navigation drift online estimation system, used to execute the multi-gyroscope redundant resonant gyroscope inertial navigation drift online estimation method as described in any one of claims 1 to 6, characterized in that, include: Gyroscope output representation acquisition module: Divides the gyroscope inertial group into two inertial groups, inertial group A and inertial group B, monitors the gyroscope state, sets the input gyroscope inertial group to pure full-angle mode, and provides the output of the estimated gyroscope inertial group; Drift estimation module: controls the estimated gyroscope inertial group to stay at different array angles, and performs drift estimation on the estimated gyroscope inertial group; Rotation estimation module: Set the estimated gyro inertial group to pure full-angle mode, use it as the input gyro inertial group, return to the drift estimation module, estimate another gyro inertial group, and complete the drift estimation.

8. An electronic device comprising a processor, a communication interface, a memory, and a communication bus, characterized in that, When the processor executes the computer program, it implements the steps of the online estimation method for multi-gyroscope redundant resonant gyroscope inertial navigation drift as described in any one of claims 1 to 6.

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