Coordinate system coarse alignment method, system and equipment of inertial sensor and medium

Abstract

The invention relates to a coordinate system coarse alignment method, system and device of an inertial sensor and a medium, and relates to the technical field of inertial navigation system.The method comprises the steps that S1, data of the inertial sensor located in a carrier in a shaking state is obtained, a specific force equation of the carrier is constructed, the specific force equation is decomposed, and a coordinate system of the inertial sensor is obtained; the inertial sensor data comprises accelerometer data and gyroscope data; s2, constructing a vector observer according to the decomposed specific force equation; and S3, solving the decomposed specific force equation in combination with the inertial sensor data and the vector observer, and completing coordinate system coarse alignment of the inertial sensor according to a solving result. According to the invention, effective coarse alignment can be carried out on the coordinate system of the inertial sensor in the carrier in a shaking state.

Description

Technical Field

[0001] The present invention relates to the technical field of inertial navigation system design, and in particular to a method, system, device and medium for rough alignment of the coordinate system of an inertial sensor. Background Art

[0002] An Inertial Navigation System (INS) can provide an information source for high-precision attitude estimation, positioning, etc. The inertial navigation system does not rely on external navigation signals (such as satellite signals), so it can work in environments without GPS or other external navigation signals, such as underwater, indoors or electromagnetic interference environments, and has a very wide range of applications.

[0003] Currently, attitude estimation of inertial navigation systems mostly adopts a self-alignment method to achieve a high-precision north-seeking goal by using the gyrocompass effect. In the process of achieving high-precision self-alignment, sensor error is the main reason affecting its accuracy. To improve the alignment accuracy, it is necessary to estimate and compensate the zero-bias error of the sensor. The zero-bias error refers to the output deviation of the sensor when there is zero input (i.e., no actual physical quantity input), which reflects the inherent offset of the sensor under static conditions. Most existing methods focus on the multi-position fine alignment process, but ignore the zero-bias error estimation in the rough alignment process, which leads to problems such as an increase in the system alignment time and the inability to exert the rough alignment efficiency.

[0004] In summary, the rough alignment process of the inertial navigation system of the existing carrier has poor accuracy and low efficiency, and it is necessary to optimize the rough alignment method. Summary of the Invention

[0005] Therefore, the technical problem to be solved by the present invention is to overcome the problems of poor accuracy and low efficiency in the rough alignment process of the inertial navigation system of the existing carrier.

[0006] To solve the above technical problem, the present invention provides a method for rough alignment of the coordinate system of an inertial sensor, including:

[0007] Step S1: Obtain inertial sensor data located in the carrier in a shaking state, construct the specific force equation of the carrier, and decompose the specific force equation. The inertial sensor data includes accelerometer data and gyroscope data;

[0008] Step S2: Construct a vector observer according to the decomposed specific force equation;

[0009] Step S3: Solve the decomposed specific force equation by combining the inertial sensor data and the vector observer, and complete the rough alignment of the coordinate system of the inertial sensor according to the solution result.

[0010] In one embodiment of the present invention, in step S1, inertial sensor data in the carrier under the shaking state is obtained by constructing an inertial sensor measurement model, and the formula is:

[0011] ;

[0012] In the formula, represents the accelerometer output acceleration; represents the true acceleration; represents the accelerometer zero bias; represents the accelerometer measurement noise; represents the gyroscope output angular velocity; represents the true angular velocity; represents the gyroscope zero bias; represents the gyroscope measurement noise.

[0013] In one embodiment of the present invention, in step S1, the specific force equation of the carrier is constructed, and the formula is:

[0014] ;

[0015] In the formula, represents the motion acceleration of the carrier; represents the direction cosine matrix from the b system to the n system; represents the mapping of the earth's angular velocity of rotation in the n system; represents the mapping of the motion angular velocity of the n system in the n system; represents the motion velocity of the carrier; represents the gravity vector;

[0016] Since the carrier is in a shaking state, the motion acceleration is ignored, and the specific force equation is simplified to:

[0017] .

[0018] In one embodiment of the present invention, the formula for decomposing the specific force equation in step S1 is:

[0019] ;

[0020] In the formula, represents the direction cosine matrix from the n0 system to the b0 system; represents the direction cosine matrix of the b system relative to the b0 system; represents the direction cosine matrix of the n system relative to the n0 system.

[0021] In one embodiment of the present invention, the method for constructing a vector observer according to the decomposed specific force equation in step S2 includes:

[0022] Construct a vector observer according to the decomposed specific force equation, and the formula is:

[0023] ;

[0024] In the formula, represents the reference vector; represents the observed vector;

[0025] Among them, the direction cosine matrix and The calculation formula is:

[0026] ;

[0027] In the formula, represents The differential of, represents The differential of, represents the mapping of the rotation angular velocity of the n - system relative to the i - system in the n - system; represents the mapping of the rotation angular velocity of the b - system relative to the i - system in the b - system; [×] represents the vector skew - symmetric matrix operation.

[0028] In an embodiment of the present invention, the method for solving the decomposed specific force equation by combining the inertial sensor data and the vector observer in the step S3 includes:

[0029] Combining the vector observer and the inertial sensor data, the calculated observed vector is:

[0030] ;

[0031] In the formula, represents the calculated observed vector; represents the direction cosine matrix of the b - system relative to the b0 - system calculated using the gyroscope output; I represents the identity matrix; t represents the alignment duration;

[0032] Expand the reference vector to get:

[0033] ;

[0034] In the formula, represents the direction cosine matrix of the n - system relative to the n0 - system;

[0035] Since the carrier is in a shaking state, the direction cosine matrices and are transpose matrices of each other: ; The direction cosine matrix The calculation formula is:

[0036] ;

[0037] In the formula, represents the direction cosine matrix of the n-system relative to the e-system; represents the local longitude; represents the local latitude;

[0038] Then the reference vector The calculation formula is:

[0039] ;

[0040] In the formula, represents the gravity value; represents the angular velocity of the Earth's rotation; represents the alignment duration; represents the equivalent matrix;

[0041] Substitute the derived reference vector into the calculated observation vector , and obtain:

[0042] ;

[0043] In the formula, ; ; , , respectively represent the three row vectors of matrix M; H represents the measurement matrix; x represents the estimated state quantity;

[0044] Construct a parameter vector model based on the estimated state quantity x and the calculated observation vector :

[0045] ;

[0046] In the formula, represents the differential of x;

[0047] Use the estimated state quantity x obtained by estimation to perform vector reconstruction on the calculated observation vector :

[0048] ;

[0049] In the formula, represents the first 9 columns of matrix H; represents the first 9 elements of; represents the optimal reconstructed observation vector;

[0050] Use the optimal reconstructed observation vector to construct the attitude matrix:

[0051] ;

[0052] Wherein, represents the attitude matrix at time k; matrix; represents the attitude matrix at time k-1; matrix; and The operation is expressed as:

[0053] ;

[0054] Wherein, represents the reference vector at time k;

[0055] For the calculated attitude Extract the attitude quaternion from the matrix, convert the attitude quaternion to get , and substitute the obtained into to coarsely align the coordinate system of the paired inertial sensors.

[0056] In an embodiment of the present invention, the method for estimating the estimated state quantity x is: estimating the estimated state quantity x in the parameter vector model through Kalman filtering, and the formula is:

[0057] ;

[0058] Wherein, represents the optimal estimated state at time k-1; represents the predicted state at time k; represents the state error covariance matrix at time k-1; represents the predicted state error covariance at time k; represents the process noise covariance matrix; represents the measurement matrix at time k; represents the measurement noise covariance matrix at time k; represents the gain matrix at time k; represents the optimal estimated state at time k; represents the calculated observation vector at time k; represents the state error covariance matrix at time k.

[0059] To solve the above technical problems, the present invention provides a system for coarsely aligning the coordinate system of inertial sensors, including:

[0060] Acquisition and construction module: It is used to acquire the inertial sensor data in the carrier in the shaking state, construct the specific force equation of the carrier, and decompose the specific force equation. The inertial sensor data includes accelerometer data and gyroscope data;

[0061] Construction module: It is used to construct a vector observer according to the decomposed specific force equation;

[0062] Alignment module: It is used to solve the decomposed specific force equation by combining the inertial sensor data and the vector observer, and complete the coarse alignment of the coordinate system of the inertial sensor according to the solution result.

[0063] To solve the above technical problems, the present invention provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned method for coarse alignment of the coordinate system of the inertial sensor are implemented.

[0064] To solve the above technical problems, the present invention provides an inertial navigation system, including the above-mentioned electronic device.

[0065] The above technical solutions of the present invention have the following advantages compared with the prior art:

[0066] The method for coarse alignment of the coordinate system of the inertial sensor according to the present invention can eliminate the sensor zero bias and make the estimation error of the sensor coarse alignment as small as possible. Especially in the shaking state, it can quickly and accurately estimate the carrier attitude and provide an initial attitude estimate for subsequent fine alignment;

[0067] The coarse alignment method adopted by the present invention has a small calculation amount and good real-time performance, and can quickly estimate the approximate attitude of the carrier. The present invention improves the navigation performance of the sensor by improving the accuracy of the coarse alignment, and can provide data reference for the subsequent improvement of the inertial navigation accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to make the content of the present invention easier to be clearly understood, the following further details the present invention according to the specific embodiments of the present invention in conjunction with the drawings.

[0069] Figure 1 is the flowchart of the method of the present invention;

[0070] Figure 2 is the comparison diagram of the pitch angle estimation error in the embodiment of the present invention;

[0071] Figure 3 is the comparison diagram of the roll angle estimation error in the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0072] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, so that those skilled in the art can better understand the present invention and be able to implement it, but the embodiments cited are not intended to limit the present invention.

[0073] Embodiment 1

[0074] Referring to Figure 1 As shown, the present invention relates to a method for rough alignment of the coordinate system of an inertial sensor. The inertial sensor is disposed in a carrier, and the carrier (such as a vehicle, a ship, etc.) is in a shaking environment (such as rocking waves, uneven road surfaces, changing airflows, etc.). The method includes:

[0075] Step S1: Obtain the inertial sensor data located in the carrier under the shaking state, construct the specific force equation of the carrier, and decompose the specific force equation. The inertial sensor data includes accelerometer data and gyroscope data;

[0076] Step S2: Construct a vector observer according to the decomposed specific force equation, and the vector observer is used to estimate the attitude of the carrier;

[0077] Step S3: Solve the decomposed specific force equation by combining the inertial sensor data and the vector observer, and complete the rough alignment of the coordinate system of the inertial sensor (equivalent to estimating the attitude of the carrier) according to the solution result.

[0078] The following is a detailed introduction to this embodiment:

[0079] First, the coordinate systems are described: The n coordinate system represents the navigation coordinate system, the n0 coordinate system represents the navigation coordinate system at the initial moment, the e coordinate system represents the earth-centered inertial coordinate system (earth-centered inertial coordinate system), the b coordinate system represents the carrier coordinate system, the b0 coordinate system represents the carrier coordinate system at the initial moment, the g coordinate system represents the local horizontal geographic coordinate system, and the i coordinate system represents the inertial coordinate system (earth-centered inertial coordinate system).

[0080] Step S1: Obtain the inertial sensor data;

[0081] Construct an inertial sensor measurement model to obtain the inertial sensor data located in the carrier under the shaking state. The formula is:

[0082] (1)

[0083] In the formula, represents the accelerometer output acceleration; represents the true acceleration; represents the accelerometer zero bias; represents the accelerometer measurement noise; represents the gyroscope output angular velocity; represents the true angular velocity; represents the gyroscope zero bias; Indicates the gyroscope measurement noise.

[0084] Construct the specific force equation to describe the motion of the vehicle, and the formula is:

[0085] (2)

[0086] In the formula, Indicates the motion acceleration of the vehicle; Indicates the direction cosine matrix from the b system to the n system; Indicates the true acceleration; Indicates the mapping of the earth's angular velocity of rotation in the n system; Indicates the mapping of the angular velocity of motion of the n system in the n system; Indicates the motion velocity of the vehicle; Indicates the gravity vector.

[0087] Considering that the vehicle is in a shaking state, the motion acceleration Can be ignored, and the above specific force equation (i.e., formula (2)) can be simplified to:

[0088] (3)

[0089] In the formula, Indicates the direction cosine matrix from the b system to the n system; Indicates the true acceleration; Indicates the gravity vector.

[0090] Adopt the direction cosine matrix Decompose the simplified specific force equation (i.e., formula (3)) to obtain:

[0091] (4)

[0092] In the formula, Indicates the true acceleration; Indicates the gravity vector; Indicates the direction cosine matrix from the n0 system to the b0 system; Indicates the direction cosine matrix of the b system relative to the b0 system; Indicates the direction cosine matrix of the n system relative to the n0 system.

[0093] It should be noted that the ultimate goal of this embodiment is to solve in formula (4). According to the obtained , the relative relationship between the vehicle coordinate system at the initial moment and the navigation coordinate system at the initial moment can be determined, and then coarse alignment can be achieved.

[0094] Step S2: Construct a vector observer;

[0095] According to the above analysis and combined with formula (4), the vector observer can be constructed as follows:

[0096] (5)

[0097] In the formula, represents the reference vector (representing the projection of gravity in the navigation coordinate system); represents the direction cosine matrix of the n - system relative to the n0 - system; represents the gravity vector; represents the observed vector (representing the projection of acceleration in the vehicle coordinate system); represents the direction cosine matrix of the b - system relative to the b0 - system; represents the true acceleration.

[0098] Among them, the direction cosine matrices and can be calculated by the following formula:

[0099] (6)

[0100] In the formula, represents differential of, represents differential of, represents the direction cosine matrix of the n - system relative to the n0 - system; represents the direction cosine matrix of the b - system relative to the b0 - system; represents the mapping of the rotation angular velocity of the n - system relative to the i - system in the n - system; represents the mapping of the rotation angular velocity of the b - system relative to the i - system in the b - system; [×] represents the vector skew - symmetric matrix operation.

[0101] Theoretically, if the vehicle attitude is correct, the observed vector should be consistent with the reference vector. If the observed vector is not consistent with the reference vector, it indicates that there is a deviation in the vehicle attitude, and the direction cosine matrix needs to be adjusted to make the two match. In short, in this embodiment, by comparing the reference vector and the observed vector, the attitude of the vehicle (i.e., the direction cosine matrix ) is deduced inversely.

[0102] Step S3: Perform parameter identification modeling and parameter estimation;

[0103] Using the above vector observer and inertial sensor data, the calculated observed vector is as follows:

[0104] (7)

[0105] In the formula, represents the calculated observed vector; represents the direction cosine matrix of the b system relative to the b0 system calculated using the gyroscope output; represents the acceleration output of the accelerometer; I represents the identity matrix; represents the gyroscope bias; t represents the alignment duration; represents the direction cosine matrix of the b system relative to the b0 system; represents the true acceleration; represents the accelerometer bias; represents the accelerometer measurement noise; represents the reference vector.

[0106] It is not difficult to find that the observed vector calculated above (i.e., Equation (7)) contains the true acceleration, bias, and noise. It is necessary to remove the bias in Equation (7) and minimize the noise as much as possible.

[0107] For the reference vector in Equation (7) perform an expansion calculation:

[0108] (8)

[0109] In the formula, represents the reference vector; represents the direction cosine matrix of the n system relative to the n0 system; represents the gravity vector; represents the direction cosine matrix of the n system relative to the n0 system;

[0110] Since the carrier is in a shaking state, therefore, the direction cosine matrices and are transpose matrices of each other, that is, they satisfy ; among them, the direction cosine matrix can be calculated using the following formula:

[0111] (9)

[0112] In the formula, represents the direction cosine matrix of the n system relative to the e system; represents the local longitude; represents the local latitude;

[0113] Therefore, the reference vector can be calculated as:

[0114] (10)

[0115] In the formula, represents the reference vector; represents the local latitude; represents the gravity value; represents the angular velocity of the Earth's rotation; represents the alignment duration; represents the equivalent matrix;

[0116] Based on the above derivation, substituting Equation (10) into Equation (7), the calculated observation vector can be expressed as:

[0117] (11)

[0118] wherein, represents the calculated observation vector; ; ; represents the direction cosine matrix of the b system relative to the b0 system calculated using the gyro output; represents the acceleration zero bias; represents the accelerometer measurement noise; , , respectively represent the three row vectors of matrix M; H represents the measurement matrix; x represents the estimated state quantity (constant);

[0119] Using the above derivation, that is, based on the estimated state quantity x and the calculated observation vector construct a parameter vector model:

[0120] (12)

[0121] wherein, x represents the estimated state quantity; represents the differential of x; represents the calculated observation vector; H represents the measurement matrix; represents the direction cosine matrix of the b system relative to the b0 system calculated using the gyro output; represents the accelerometer measurement noise;

[0122] The estimation of the estimated state quantity x in the parameter vector model (i.e., Equation (12)) can be achieved through Kalman filtering:

[0123] (13)

[0124] wherein, represents the optimal estimated state at time k-1; represents the predicted state at time k; represents the state error covariance matrix at time k-1; represents the predicted state error covariance at time k; represents the process noise covariance matrix; represents the measurement matrix at time k; Denote the measurement noise covariance matrix at time k; Denote the gain matrix at time k; Denote the optimal estimated state at time k; Denote the calculated observation vector at time k; Denote the state error covariance matrix at time k;

[0125] Use the estimated state quantity x obtained from the estimation to perform vector reconstruction on the calculated observation vector (i.e., Equation (12)), the purpose of vector reconstruction is to remove the zero bias in Equation (7) and minimize the noise as much as possible, expressed as:

[0126] (14)

[0127] In the formula, Denote the first 9 columns of matrix H; Denote The first 9 elements of; Denote the optimal reconstructed observation vector;

[0128] Based on the above analysis, the attitude matrix can be constructed using the optimal reconstructed observation vector:

[0129] (15)

[0130] In the formula, Denote the attitude at time k matrix; Denote the attitude at time k - 1 matrix; and The operation can be expressed by the following formula:

[0131] (16)

[0132] In the formula, Denote the reference vector at time k; Denote the optimal reconstructed observation vector;

[0133] Finally, extract the attitude quaternion from the calculated attitude matrix, and the calculation result is as follows:

[0134] (17)

[0135] In the formula, Denote the attitude at time k matrix; Denote the attitude quaternion from the n0 system to the b0 system; Denote the eigenvalue; from the attitude According to the basic principle of the matrix, the eigenvector corresponding to the maximum eigenvalue is the optimal attitude quaternion. Therefore, the maximum eigenvalue is calculated using formula (17), and then the corresponding quaternion can be obtained. After calculating the quaternion, the following formula can be used to convert the quaternion to the direction cosine matrix Conversion:

[0136] (18)

[0137] represents the direction cosine matrix from the n0 system to the b0 system; among them, ; and substitute the obtained into for rough alignment of the coordinate system of the paired inertial sensors.

[0138] After step S3, it also includes:

[0139] If the time k is greater than or equal to the alignment duration t, the alignment result is output; if the time k is less than the alignment duration t, the process of repeating steps S1 to S3 is repeated until the alignment ends.

[0140] The experimental analysis is as follows:

[0141] The present invention effectively eliminates the influence of sensor zero bias, and the reconstructed vector has less noise. Figure 2 is the comparison chart of pitch angle error (the abscissa is time / S, and the ordinate is the pitch error corresponding to the pitch angle / deg). It can be seen from Figure 2 (the number 1 represents the traditional method, and the number 2 represents this embodiment) that compared with the traditional method, this embodiment has a smaller estimation error, removes the sensor zero bias from the alignment result, and realizes unbiased estimation. Figure 3 is the comparison chart of roll angle error (the abscissa is time / S, and the ordinate is the roll error corresponding to the roll angle / deg). It can be seen from Figure 3 (the number 1 represents the traditional method, and the number 2 represents this embodiment) that this embodiment can effectively eliminate the bias error caused by sensor zero bias and improve the alignment accuracy.

[0142] Embodiment 2

[0143] This embodiment provides a rough alignment system for the coordinate system of inertial sensors, including:

[0144] Acquisition and construction module: used to acquire inertial sensor data located in the carrier under the shaking state, construct the specific force equation of the carrier, and decompose the specific force equation. The inertial sensor data includes accelerometer data and gyroscope data;

[0145] Construction module: used to construct a vector observer according to the decomposed specific force equation;

[0146] Alignment module: It is used to solve the decomposed specific force equation by combining the inertial sensor data and the vector observer, and complete the rough alignment of the coordinate system of the inertial sensor according to the solution result.

[0147] Embodiment III

[0148] This embodiment provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the method for rough alignment of the coordinate system of the inertial sensor in Embodiment I.

[0149] Embodiment IV

[0150] This embodiment provides an inertial navigation system, including the electronic device as described in Embodiment III.

[0151] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) containing computer-usable program code. The solutions in the embodiments of the present application can be implemented in various computer languages. For example, object-oriented programming languages such as Java and interpreted scripting languages such as JavaScript.

[0152] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0153] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including instruction means, and the instruction means implements the functions in Figure 1 one or more flows and / or blocks Figure 1The functions specified in one or more boxes.

[0154] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide for implementing the steps of the functions specified in one Figure 1 One process or more processes and / or boxes Figure 1 The steps of the functions specified in one or more boxes.

[0155] Although the preferred embodiments of the present application have been described, those skilled in the art can make additional changes and modifications to these embodiments once they learn the basic creative concepts. Therefore, the appended claims are intended to be construed as including the preferred embodiments as well as all changes and modifications falling within the scope of the present application.

[0156] Obviously, the above embodiments are merely examples for clear illustration and are not limitations on the implementation manners. For those of ordinary skill in the art, other different forms of changes or variations can be made based on the above description. It is not necessary and impossible to enumerate all the implementation manners here. And the obvious changes or variations derived therefrom are still within the protection scope of the present invention.

Claims

1. A method for coarsely aligning a coordinate system of an inertial sensor, characterized in that: include: Step S1: acquiring inertial sensor data located in the carrier in a shaking state, constructing a specific force equation of the carrier, and decomposing the specific force equation, wherein the inertial sensor data includes accelerometer data and gyroscope data; Step S2: construct a vector observer according to the decomposed specific force equation; Step S3: solving the decomposed specific force equation in combination with the inertial sensor data and the vector observer, and completing the coarse alignment of the coordinate system of the inertial sensor according to the solution result.

2. The method for coarsely aligning the coordinate system of an inertial sensor according to claim 1, characterized in that: The method for obtaining the inertial sensor data located in the carrier in the shaking state in step S1 includes: obtaining the inertial sensor data by constructing an inertial sensor, and the formula is: ； In the formula, Indicates the accelerometer output acceleration; represents the true acceleration; Indicates acceleration zero bias; represents the accelerometer measurement noise; Indicates the gyroscope output angular velocity; represents the true angular velocity; Indicates the gyroscope zero bias; represents the gyroscope measurement noise.

3. The method for coarsely aligning the coordinate system of an inertial sensor according to claim 2, characterized in that: The specific force equation of the carrier is constructed in step S1, and the formula is: ； In the formula, Indicates the carrier's motion acceleration; Represents the direction cosine matrix from b system to n system; Represents the mapping of the Earth's rotation angular velocity in the n system; It represents the mapping of the angular velocity of the n-system motion in the n-system; Indicates the moving speed of the carrier; represents the gravity vector; Since the carrier is in a shaking state, the motion acceleration is ignored. , then the specific force equation is simplified to: 。 4. The method for coarsely aligning the coordinate system of an inertial sensor according to claim 3, characterized in that: The formula for decomposing the contrast equation in step S1 is: ； In the formula, Represents the direction cosine matrix from n0 system to b0 system; Represents the direction cosine matrix of the b system relative to the b0 system; Represents the direction cosine matrix of the n system relative to the n0 system.

5. The method for coarsely aligning the coordinate system of an inertial sensor according to claim 4, characterized in that: The method for constructing a vector observer according to the decomposed specific force equation in step S2 includes: The vector observer is constructed according to the decomposed specific force equation, and the formula is: ； In the formula, represents the reference vector; represents the observation vector; Among them, the direction cosine matrix and The calculation formula is: ； In the formula, express The differential of express The differential of It represents the mapping of the rotational angular velocity of the n system relative to the i system in the n system; It represents the mapping of the angular velocity of rotation of system b relative to system i in system b; [×] represents the operation of vector conversion to skew-symmetric matrix.

6. The method for coarsely aligning the coordinate system of an inertial sensor according to claim 5, characterized in that: The method for solving the decomposed specific force equation in step S3 by combining the inertial sensor data and the vector observer includes: Combining the vector observer and inertial sensor data, the calculated observation vector is: ； In the formula, represents the calculated observation vector; represents the direction cosine matrix of the b system relative to the b0 system calculated using the gyroscope output; I represents the unit matrix; t represents the alignment duration; For reference vector Expand it to get: ； In the formula, Represents the direction cosine matrix of the n system relative to the n0 system; Since the carrier is in a shaking state, the direction cosine matrix and Transposed matrices: ; Direction cosine matrix The calculation formula is: ； In the formula, Represents the direction cosine matrix of the n system relative to the e system; Indicates the local longitude; Indicates the local latitude; The reference vector The calculation formula is: ； In the formula, Indicates the gravity value; represents the angular velocity of the Earth's rotation; Indicates alignment duration; represents the equivalent matrix; The derived reference vector Substitute the observation vector into the calculation ,get: ； In the formula, ; ; , , They represent the three row vectors of the matrix M respectively; H represents the measurement matrix; x represents the estimated state quantity; Based on the estimated state x and the calculated observation vector Construct a parametric vector model: ； In the formula, represents the differential of x; The estimated state quantity x is used to calculate the observation vector Perform vector reconstruction: ； In the formula, Represents the first 9 columns of matrix H; express The first 9 elements of ; represents the optimally reconstructed observation vector; Using the optimally reconstructed observation vector Construction posture matrix: ； In the formula, represents the posture at time k matrix; represents the posture at time k-1 matrix; and The operation is expressed as: ； In the formula, represents the reference vector at time k; The calculated posture The matrix extracts the attitude quaternion and converts the attitude quaternion into , and the solved Substitution , to coarsely align the coordinate systems of paired inertial sensors.

7. The method for coarsely aligning the coordinate system of an inertial sensor according to claim 6, characterized in that: The method for estimating the estimated state quantity x is: estimating the estimated state quantity x in the parameter vector model by Kalman filtering, and the formula is: ； In the formula, Represents the optimal estimation state at time k-1; represents the predicted state at time k; represents the state error covariance matrix at time k-1; represents the covariance of the predicted state error at time k; represents the process noise covariance matrix; represents the measurement matrix at time k; represents the measurement noise covariance matrix at time k; represents the gain matrix at time k; represents the optimal estimated state at time k; represents the observation vector calculated at time k; represents the state error covariance matrix at time k.

8. A coordinate system coarse alignment system for an inertial sensor, characterized in that: include: Acquisition and construction module: used to acquire the inertial sensor data located in the carrier under the shaking state, construct the specific force equation of the carrier, and decompose the specific force equation. The inertial sensor data includes accelerometer data and gyroscope data; Building module: used to build a vector observer based on the decomposed specific force equation; Alignment module: used to solve the decomposed specific force equation in combination with the inertial sensor data and the vector observer, and to perform rough alignment of the coordinate system of the inertial sensor according to the solution result.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method for coarse alignment of the coordinate system of the inertial sensor according to any one of claims 1 to 7 are implemented.

10. An inertial navigation system, characterized in that: Comprising the electronic device as claimed in claim 9.

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