Rapid high-precision transfer alignment method for composite inertial system

Abstract

The invention relates to a rapid high-precision transfer alignment method for a composite inertial system, and belongs to the technical field of initial attitude reference establishment of a movable base of a composite inertial navigation system with a rotating mechanism. According to the method, a high-order transfer alignment Kalman filtering model is constructed, high-precision estimation of a table body attitude misalignment angle of the composite inertial system is realized, meanwhile, an installation error and flexural deflection between a master inertial navigation and a slave inertial navigation are estimated and compensated, and the alignment performance is improved by fully utilizing a high-precision attitude reference; according to the invention, the problems of long alignment time and low precision of the existing composite inertial navigation in the aspect of transfer alignment of the movable base are solved; the method can be applied to the initial attitude reference establishment process of the moving base of a double-axis and three-axis composite inertial system, and has high rapidity and alignment precision.

Description

A fast and high-precision transfer alignment method for composite inertial systems Technical Field

[0001] This invention relates to a rapid and high-precision transfer alignment method for a composite inertial system, belonging to the technical field of establishing the initial attitude reference of a moving base for a composite inertial navigation system with a rotating mechanism. Background Technology

[0002] The composite inertial system is a new type of inertial system. It is equipped with three high-precision fiber optic gyroscopes, which can directly output the angular rate of the carrier relative to the inertial space. It has a three-axis, two-frame rotation mechanism, which can not only keep the carrier stable relative to the inertial space, but also control the carrier to rotate according to a predetermined rotation control strategy during operation. At the same time, it can use the output of accelerometers and gyroscopes to directly perform strapdown calculations on the carrier.

[0003] After years of development, transfer alignment technology has achieved significant progress in error models, matching methods, observability analysis, lever effects, and flexural deformation, greatly improving the speed and accuracy of transfer alignment. In practical engineering applications, transfer alignment technology is widely used in ships, tactical weapons, and aircraft. However, the sub-inertial navigation systems (INS) studied in these fields are mostly strapdown INS. Due to application background and other reasons, there is limited discussion both domestically and internationally regarding the use of composite inertial systems in sub-INS. Domestic research in transfer alignment technology mainly focuses on airborne and shipborne platforms, often employing a "velocity + attitude" matching scheme to improve alignment speed. During alignment, the carrier needs to perform specific trajectory maneuvers, such as O-shaped, S-shaped, or port and starboard roll maneuvers, to achieve short convergence time and high accuracy.

[0004] Traditional frame-based inertial navigation systems still rely on optical aiming schemes for alignment transfer. This necessitates the installation of complex optical paths on ships and regular calibration, posing significant challenges to user operation and making it difficult to meet the demands of current digital and intelligent development. For dynamic alignment transfer inertial navigation systems using three-axis fiber optic gyroscopes, existing solutions have implemented digital alignment technology based on velocity + position matching. This eliminates the need for specific maneuvers by the carrier during alignment; however, this solution has a long convergence time and does not account for the effects of carrier arm changes and deflection. The requirements of next-generation weapon systems for rapid launch and reduced preparation time place higher demands on the speed and accuracy of alignment transfer, making traditional velocity + position matching alignment solutions insufficient for these new needs. Summary of the Invention

[0005] The technical problem solved by this invention is to overcome the shortcomings of the prior art and provide a rapid and high-precision transfer alignment method for a composite inertial system. Under the condition of various disturbances caused by the movement of the base during the carrier's movement, the initial attitude reference of the composite inertial guidance base can be established in a short time, thereby improving the rapid response capability and alignment accuracy of weapon equipment.

[0006] The technical solution of this invention is as follows: A rapid and high-precision transfer alignment method for a composite inertial system, comprising: S1, constructing a transfer alignment test control system using a main inertial navigation system with speed and attitude information output and a composite inertial system; powering on and heating the transfer alignment test control system and initializing its parameters; controlling the rotation mechanism of the composite inertial system to rotate to the zero position to enter the transfer alignment process; S2, calculating the interference angular motion information of the platform based on the gyroscope output signal of the composite inertial system, and then applying a corresponding control torque to the rotation mechanism to isolate the platform from the external interference angular motion of the corresponding axis; S3, applying control commands to the rotation mechanism to control the platform to rotate and stop according to a predetermined rotation path, while simultaneously controlling the carrier to perform a maneuvering sway according to specified angular motion conditions; S4, real-time acquisition of gyroscope, accelerometer, and frame angle data signals of the composite inertial system and the synchronization signal, speed, and attitude signal of the main inertial navigation system, and aligning the measurement data of the composite inertial system with the data of the main inertial navigation system based on the synchronization signal; S5, utilizing the composite inertial system... S6. Coarse alignment is performed using inertial measurement data of the system to obtain the initial attitude matrix of the platform relative to the navigation coordinate system; S7. The initial attitude reference is established using the coarse alignment result, and it is determined whether the navigation calculation time has been reached. If it has been reached, navigation calculation is performed using inertial measurement data, and the state matrix of the fine alignment Kalman filter is updated in real time; S8. It is determined whether the filtering time has been reached. If it has been reached, the velocity and attitude information of the main inertial navigation system received at the current time are matched with the navigation calculation result of the composite inertial navigation system after dynamic error compensation, the observation and observation matrix of the fine alignment Kalman filter are calculated, the Kalman filter equation is updated, and the state quantity estimate is calculated; S9. It is determined whether the alignment end time has been reached. If not, the velocity error, main inertial navigation system installation error, and deflection angle are estimated by the Kalman filter to perform real-time feedback correction on the composite inertial navigation system; if so, the alignment ends, and the attitude misalignment angle estimated by the Kalman filter is used to compensate and correct the navigation result of the platform to obtain the alignment result of the composite inertial system.

[0007] In the above-mentioned rapid and high-precision transfer alignment method for a composite inertial system, in step S2, the open-loop transfer function of the control loop that isolates the stage from external interference angular motion along the corresponding axis is:

[0008] in, Let the moment of inertia of the rotating mechanism's shaft be _____. This refers to the transfer function of the fiber optic gyroscope. For loop correction network, This is the power stage amplification factor. For the shaft-end torque motor transfer function, This represents the gain coefficient of the fiber optic gyroscope. This is the gain coefficient of the torque motor. is the time constant of the torque motor.

[0009] In the above-mentioned rapid and high-precision transfer alignment method of the composite inertial system, in step S3, the rotation path includes two dwelling positions and two rotation processes. First, the platform is locked to the frame at a 180° position around the outer ring axis. After rotating to the position, the control platform is in an isolation angle motion state and dwells for a period of time. Then, it rotates 180° clockwise around the outer ring axis to the frame at position 0 and dwells for a period of time. At the same time, the carrier is controlled to swing in the horizontal direction.

[0010] In the above-mentioned rapid and high-precision transfer alignment method for composite inertial systems, step S4 involves real-time acquisition of gyroscope, accelerometer, and frame angle data signals from the composite inertial system, as well as synchronization signals, velocity, and attitude signals from the main inertial navigation system. The method aligns the measurement data of the composite inertial system with the data from the main inertial navigation system based on the synchronization signal. This includes: the composite inertial navigation system acquiring the periodic square wave signal output by the main inertial navigation system; defining the first falling edge of the synchronization signal received by the composite inertial navigation system as the start time after the transfer alignment process begins; aligning the inertial measurement data received at this time with the velocity and attitude data of the main inertial navigation system; and performing data alignment once at each subsequent falling edge.

[0011] In the aforementioned rapid and high-precision transfer alignment method for a composite inertial system, step S5 involves using inertial measurement data from the composite inertial system for coarse alignment to obtain the initial attitude matrix of the platform relative to the navigation coordinate system. This includes calculating a relatively accurate initial attitude information using a multi-vector attitude determination analytical coarse alignment method. The solution method is as follows: calculating the platform system velocity vector and the navigation system velocity vector. Value:

[0012] in, and Let represent velocity and velocity increment respectively, T represent sampling period, subscript i represent the i-th sampling time, and superscript g represent projection in the navigation system; The number of samples, for The transformation matrix from the time-stage system to the solidification stage system. For angular increments, for The transformation matrix from the time-based navigation frame to the solidified navigation frame. For navigation system speed, For a moment, As a unit array, The projection of the rotational angular velocity of the navigation frame relative to the inertial frame onto the navigation frame. The projection of gravitational acceleration onto the navigation system. Project the Earth's rotational angular velocity onto the navigation frame; calculate the values ​​at multiple moments. According to the relation The least squares method was used to fit the data. The result is that the initial attitude matrix of the platform relative to the navigation coordinate system is solved as follows:

[0013] in, The attitude transfer matrix from the solidification stage to the solidification stage; Let be the attitude transition matrix from the fixed navigation frame to the initial navigation frame; Let be the attitude transition matrix from the initial navigation frame to the current navigation frame. Let be the attitude transfer matrix from the solidified stage system to the solidified navigation system.

[0014] In the above-mentioned fast and high-precision transfer alignment method for composite inertial systems, in step S6, the state equation of the fine alignment Kalman filter is:

[0015] in, These are the state variables and their derivatives, respectively. The state matrix; For system noise; the formula for updating the state matrix of the precisely aligned Kalman filter is:

[0016] in, This is a one-step prediction of the state at time k. Here is the filter state transition matrix. This is an estimate of the state at time k-1. The variance matrix for one-step prediction. For the estimated variance matrix, This is the system noise driving matrix.

[0017] In the above-mentioned rapid and high-precision transfer alignment method for composite inertial systems, in step S7, the dynamic error compensation uses a second-order Gaussian-Markov process to describe the deflection motion, and the deformation processes in the three directions are independent of each other. The deflection deformation compensation model is as follows:

[0018] in, It is Gaussian white noise with variance of ; The angular velocity of the flexural deformation; The elastic coefficient of the deformable structure of the carrier; Let be the deflection angle, and let be the root mean square. ,satisfy .

[0019] Dynamic lever arm effect error Represented as:

[0020] in, Main and secondary inertial guide arms, The angular velocity of the carrier relative to the inertial frame of reference. For time.

[0021] The dynamic installation error compensation model is as follows:

[0022] in, The main inertial navigation system installation error angle For dynamic flexural deformation angle, For the installation error matrix, The identity matrix is ​​used; the observation equation for the precisely aligned Kalman filter is:

[0023] in, For state variables, For observation purposes, For the observation matrix, To observe noise; the formula for calculating the measurement update of the precise aligned Kalman filter is:

[0024] in, This is the optimal estimate of the state at time k. This is a one-step prediction of the state at time k. Here is the filter gain matrix. For observation purposes, For the observation matrix, The variance matrix for one-step prediction. To measure the noise variance matrix, The variance matrix is ​​the optimal estimate. It is a unit array.

[0025] In the above-mentioned rapid and high-precision transfer alignment method for composite inertial systems, step S8 involves using a Kalman filter to estimate the velocity error, the main inertial navigation system installation error, and the deflection angle to perform feedback correction on the composite inertial system. This includes the following velocity correction formula:

[0026] in, This represents the velocity before and after Kalman filter feedback compensation at time k; These are the estimated velocity errors in the three directions of the navigation coordinate system; the attitude correction formula is:

[0027] in, To compensate for the attitude error matrix from the sub-inertial navigation system to the main inertial navigation system, The initial values ​​of the attitude error matrix from the sub-inertial navigation system to the main inertial navigation system are given. The attitude error compensation matrix for the master and sub-inertial navigation systems;

[0028] in, These represent the estimated installation error angles of the main and sub-inertial navigation systems in the x, y, and z directions, respectively. These represent the estimated values ​​of the flexural deformation angles in the x, y, and z directions, respectively.

[0029] In the aforementioned fast and high-precision transfer alignment method for a composite inertial system, step S8 involves using the attitude misalignment angle estimated by a Kalman filter to compensate and correct the stage navigation results, thereby obtaining the transfer alignment results of the composite inertial system. This includes obtaining the stage attitude matrix at the end of the alignment process based on the fine alignment navigation calculation results. The calculation method for the sub-INS attitude misalignment angle compensation matrix based on the precisely aligned Kalman filter estimation value is as follows:

[0030] in, Let x, y, and z represent the estimated values ​​of the sub-inertial navigation attitude misalignment angles, respectively. The calculation method for the transferred alignment result, based on the platform attitude matrix and the misalignment angle compensation matrix, is as follows:

[0031] in, To compensate for the background body pose matrix, i.e. to transmit the alignment result.

[0032] A composite inertial system for rapid and high-precision transfer alignment includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the above-described method.

[0033] Compared with the prior art, the present invention has at least the following beneficial effects: (1) The embodiments of the present invention provide a fast and high-precision transfer alignment method for composite inertial systems. Using the velocity and attitude information provided by the high-precision master inertial navigation system as a reference, a high-order transfer alignment Kalman filter model is constructed by adopting the "velocity + attitude" matching method to achieve high-precision estimation of the attitude misalignment angle of the composite inertial system platform. At the same time, the installation error and deflection deformation between the master and slave inertial navigation systems are estimated and compensated, and the high-precision attitude reference is fully utilized to improve the alignment performance. The present invention solves the problem of long alignment time and low accuracy of existing composite inertial navigation systems in the transfer alignment of moving bases. The present invention can be applied to the initial attitude reference establishment process of the moving base of dual-axis and tri-axis composite inertial systems, and has high speed and alignment accuracy.

[0034] (2) The present invention provides a fast and high-precision transfer alignment method for a composite inertial system, which is used in the transfer alignment of a moving base of a three-axis composite inertial system. It can replace the traditional optical aiming scheme, greatly reduce the equipment support requirements and operation difficulty, and improve the operability for users.

[0035] (3) The present invention provides a fast and high-precision transfer alignment method for a composite inertial system. It adopts the optimal estimation transfer alignment method based on velocity and attitude matching using Kalman filtering. At the same time, it performs fine modeling and compensation for dynamic errors such as master inertial guide arm effect and deflection deformation, which can significantly shorten the convergence time of attitude misalignment angle and has better speed.

[0036] (4) This invention provides a fast and high-precision transfer alignment method for a composite inertial system. It adopts a three-axis inertial space-stable rotation control strategy, and controls the control body to isolate external angular motion, which can reduce the influence of carrier angular motion on transfer alignment and improve the accuracy of transfer alignment.

[0037] (5) The present invention is based on a composite inertial system with a multi-axis rotation mechanism, which can control the body to rotate around the celestial axis to improve the observability of the system. At the same time, the composite inertial system can isolate the angular motion of the carrier in the space stable mode and remain stable relative to the inertial space, which can eliminate or reduce the impact of external disturbances on the accuracy of the instrument. Attached Figure Description

[0038] Figure 1 is a schematic diagram of the fast and high-precision transfer alignment method of the composite inertial system in an embodiment of the present invention; Figure 2 is a diagram of the rotation process in an embodiment of the present invention; Figure 3 is a diagram of the angular motion conditions applied to the carrier in an embodiment of the present invention; Figure 4 is a diagram of the time allocation for coarse alignment and fine alignment in an embodiment of the present invention; Figure 5 is a flowchart of the fine alignment module in an embodiment of the present invention. Detailed Implementation

[0039] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments: The present invention overcomes the influence of various low-frequency disturbances caused by carrier motion in dynamic environments, and takes into account factors such as carrier flexure deformation and lever arm effect, and provides a fast and high-precision transfer alignment method for composite inertial systems, so as to realize the rapid establishment of the initial attitude reference of the composite inertial navigation base and meet the requirements of rapid launch.

[0040] The alignment scheme of this invention employs a Kalman filter-based optimal estimation method based on "velocity + attitude" matching to perform real-time filtering estimation of the attitude misalignment angle of the composite inertial navigation system. Specifically, it uses the velocity and attitude errors output by the main and sub-inertial navigation systems as observables, estimates the error parameters through a Kalman filter, and improves the observability of the filter by applying specific maneuvers to the carrier, thus achieving high-precision alignment in dynamic environments. The overall scheme principle block diagram is shown in Figure 1.

[0041] The rapid and high-precision transfer alignment method of the composite inertial system in this embodiment of the invention includes the following steps: S1, constructing a transfer alignment test control system using a main inertial navigation system with speed and attitude information output and a composite inertial system, powering on and heating the transfer alignment test control system, initializing the parameters, and controlling the rotation mechanism of the composite inertial system to rotate to the zero position to enter the transfer alignment process.

[0042] S2. Based on the gyroscope output signal of the composite inertial system, calculate the disturbance angular motion information of the platform, and then apply the corresponding control torque to the rotating mechanism to isolate the platform from the external disturbance angular motion of the corresponding axis.

[0043] In this embodiment, the open-loop transfer function of the control loop that isolates the platform from external disturbance angular motion along the corresponding axis is:

[0044] in, Let the moment of inertia of the rotating mechanism's shaft be _____. This refers to the transfer function of the fiber optic gyroscope. For loop correction network, This is the power stage amplification factor. For the shaft-end torque motor transfer function, What is the gain coefficient of the fiber optic gyroscope? What is the gain coefficient of the torque motor? is the time constant of the torque motor.

[0045] S3. Apply control commands to the rotating mechanism, and control the console body to rotate and stay along the predetermined rotation path, while controlling the carrier to perform mechanical swaying according to the specified angular motion conditions.

[0046] In this embodiment, the rotation process is shown in Figure 2. The rotation path includes two dwelling positions and two rotation processes. First, the platform is locked to the frame at a 180° position around the outer ring axis. After rotating to the position, the control platform is in an isolation angle motion state and stays for a period of time. Then, it rotates 180° clockwise around the outer ring axis to the frame at position 0 and stays for a period of time. At the same time, the carrier is controlled to swing in the horizontal direction.

[0047] S4. Real-time acquisition of gyroscope, accelerometer, and frame angle data signals of the composite inertial system, as well as synchronization signals, velocity, and attitude signals of the main inertial navigation system, and alignment of the composite inertial system measurement data with the main inertial navigation system data based on the synchronization signals.

[0048] In this embodiment, the gyroscope, accelerometer, and frame angle data signals of the composite inertial system and the synchronization signal, velocity, and attitude signals of the main inertial navigation system are acquired in real time. The measurement data of the composite inertial system is aligned with the data of the main inertial navigation system according to the synchronization signal. This includes: the composite inertial navigation system acquires the periodic square wave signal output by the main inertial navigation system. When the alignment process begins, the first falling edge of the synchronization signal received by the composite inertial navigation system is defined as the start time. The inertial measurement data received at this time is aligned with the velocity and attitude data of the main inertial navigation system. Data alignment is performed once at each subsequent falling edge.

[0049] S5. Use the inertial measurement data of the composite inertial system to perform coarse alignment and obtain the initial attitude matrix of the platform relative to the navigation coordinate system.

[0050] In this embodiment, coarse alignment is performed using inertial measurement data from a composite inertial system to obtain the initial attitude matrix of the platform relative to the navigation coordinate system. This includes: calculating a relatively accurate initial attitude information using a multi-vector attitude determination analytical coarse alignment method. The solution method is as follows: calculating the platform system velocity vector and the navigation system velocity vector. Value:

[0051] in, and Let represent velocity and velocity increment respectively, T represent sampling period, subscript i represent the i-th sampling time, and superscript g represent projection in the navigation system; The number of samples, for The transformation matrix from the time-stage system to the solidification stage system. For angular increments, for The transformation matrix from the time-based navigation frame to the solidified navigation frame. For navigation system speed, For a moment, As a unit array, The projection of the rotational angular velocity of the navigation frame relative to the inertial frame onto the navigation frame. The projection of gravitational acceleration onto the navigation system. Project the Earth's rotational angular velocity onto the navigation frame; calculate the values ​​at multiple moments. According to the relation The least squares method was used to fit the data. The result is that the initial attitude matrix of the platform relative to the navigation coordinate system is solved as follows:

[0052] in, The attitude transfer matrix from the solidification stage to the solidification stage; Let be the attitude transition matrix from the fixed navigation frame to the initial navigation frame; Let be the attitude transition matrix from the initial navigation frame to the current navigation frame. Let be the attitude transfer matrix from the solidified stage system to the solidified navigation system.

[0053] S6. Establish an initial attitude reference using the coarse alignment result, determine whether the navigation calculation time has been reached. If it has been reached, perform navigation calculation using inertial measurement data, and update the state matrix of the fine alignment Kalman filter in real time, then proceed to step S7; otherwise, proceed directly to step S7.

[0054] In this embodiment, the state equation of the precisely aligned Kalman filter is:

[0055] in, These are the state variables and their derivatives, respectively. The state matrix; For system noise; the formula for updating the state matrix of the precisely aligned Kalman filter is:

[0056] in, This is a one-step prediction of the state at time k. Here is the filter state transition matrix. This is an estimate of the state at time k-1. The variance matrix for one-step prediction. For the estimated variance matrix, This is the system noise driving matrix.

[0057] S7. Determine whether the filtering time has been reached. If it has, use the main inertial navigation velocity and attitude information received at the current time, after dynamic error compensation, to match it with the navigation solution of the composite inertial navigation system, calculate the precise alignment Kalman filter observation and observation matrix, update the Kalman filter equation, calculate the state quantity estimate, and then proceed to step S8; otherwise, proceed directly to step S8.

[0058] In this embodiment, dynamic error compensation uses a second-order Gaussian-Markov process to describe the flexural motion, and the deformation processes in the three directions are independent of each other. The flexural deformation compensation model is as follows:

[0059] in, It is Gaussian white noise with variance of ; The angular velocity of the flexural deformation; The elastic coefficient of the deformable structure of the carrier; Let be the deflection angle, and let be the root mean square. ,satisfy .

[0060] Dynamic lever arm effect error Represented as:

[0061] in, Main and secondary inertial guide arms, The angular velocity of the carrier relative to the inertial frame of reference. For time.

[0062] The dynamic installation error compensation model is as follows:

[0063] in, The main inertial navigation system installation error angle For dynamic flexural deformation angle, For the installation error matrix, The identity matrix is ​​used; the observation equation for the precisely aligned Kalman filter is:

[0064] in, For state variables, For observation purposes, For the observation matrix, To observe noise; the formula for calculating the measurement update of the precise aligned Kalman filter is:

[0065] in, This is the optimal estimate of the state at time k. This is a one-step prediction of the state at time k. Here is the filter gain matrix. For observation purposes, For the observation matrix, The variance matrix for one-step prediction. To measure the noise variance matrix, The variance matrix is ​​the optimal estimate. It is a unit array.

[0066] S8. Determine whether the alignment end time has been reached. If not, use the Kalman filter to estimate the velocity error, master inertial navigation system installation error, and deflection angle to perform real-time feedback correction on the composite inertial navigation system. If yes, end the alignment and use the attitude misalignment angle estimated by the Kalman filter to compensate and correct the navigation results of the platform, thus obtaining the alignment result transmitted by the composite inertial system.

[0067] In this embodiment, the composite inertial system is corrected by feedback using a Kalman filter to estimate velocity error, master inertial navigation system installation error, and deflection angle. The velocity correction formula is as follows:

[0068] in, This represents the velocity before and after Kalman filter feedback compensation at time k; These are the estimated velocity errors in the three directions of the navigation coordinate system; the attitude correction formula is:

[0069] in, To compensate for the attitude error matrix from the sub-inertial navigation system to the main inertial navigation system, The initial values ​​of the attitude error matrix from the sub-inertial navigation system to the main inertial navigation system are given. The attitude error compensation matrix for the master and sub-inertial navigation systems;

[0070] in, These represent the estimated installation error angles of the main and sub-inertial navigation systems in the x, y, and z directions, respectively. These represent the estimated values ​​of the flexural deformation angles in the x, y, and z directions, respectively.

[0071] In this embodiment, the attitude misalignment angle estimated by the Kalman filter is used to compensate and correct the navigation results of the platform, resulting in the alignment result of the composite inertial system. This includes: obtaining the platform attitude matrix at the end of the alignment based on the fine alignment navigation calculation results. The calculation method for the sub-INS attitude misalignment angle compensation matrix based on the precisely aligned Kalman filter estimation value is as follows:

[0072] in, Let x, y, and z represent the estimated values ​​of the sub-inertial navigation attitude misalignment angles, respectively. The calculation method for the transferred alignment result, based on the platform attitude matrix and the misalignment angle compensation matrix, is as follows:

[0073] in, To compensate for the background body pose matrix, i.e. to transmit the alignment result.

[0074] This invention provides a composite inertial system fast and high-precision transfer alignment device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the above-described method.

[0075] The embodiment of the present invention provides a fast and high-precision transfer alignment method for a composite inertial system, which includes the following steps: (1) Powering on and heating the composite inertial system. After the temperature stabilizes and meets the working conditions, parameter initialization is performed, and the three-axis frame is locked to zero to enter the transfer alignment process.

[0076] (2) The table body rotation control applies control commands to the composite inertial navigation rotation mechanism to make the table body rotate to the designated position and stay for a period of time. The rotation process is shown in Figure 2. It includes two dwelling positions and two rotation processes. The table body starts from the zero position and rotates 180° around the outer ring axis each time, for a total of 2 rotations. The rotation angular rate is 15° / s. After rotating to each position, the table body is in a spatially stable state and stays for a period of time. The total time for the entire alignment process is 5 minutes.

[0077] (3) Applying specific angular motion excitation to the carrier is to effectively excite the dynamic errors between the master and sub-inertial navigation systems, such as lever arm effect error and flexural deformation angle. It is necessary to control the carrier to swing around the horizontal axis at a certain angle, as shown in Figure 3. Moreover, the larger the swing angle, the better the effect on improving the observability of the system.

[0078] (4) Real-time acquisition of composite inertial navigation accelerometer, gyroscope, frame angle data signals and high-precision main inertial navigation system synchronization signal, velocity and attitude signal, and alignment of composite inertial navigation data with main inertial navigation data according to synchronization signal.

[0079] (5) Coarse alignment calculation The sampling time allocation for the coarse and fine alignment processes is shown in Figure 4. Coarse alignment calculation is performed using the composite inertial navigation inertial measurement data and the main inertial navigation sampling data during the coarse alignment process to calculate the initial attitude matrix of the composite inertial navigation platform relative to the navigation coordinate system.

[0080] (6) Fine Alignment Calculation The flowchart of the fine alignment process is shown in Figure 5. The navigation solution for the fine alignment process is performed using the coarse alignment results and composite inertial navigation measurement data, and the state matrix of the Kalman filter is updated in real time.

[0081] The 24-dimensional state variables selected in the precise quasi-Kalman filter are:

[0082] in, Indicates the attitude misalignment angle. Indicates speed error, This indicates the zero bias error of the gyroscope. This indicates the zero bias error of the accelerometer. These represent the installation error of the main inertial navigation system and the arm error, respectively. These represent the flexural deformation angle and flexural deformation angular velocity of the carrier, respectively.

[0083] The flexural deformation model of the carrier is a second-order Gaussian-Markov process, and the deformation processes in the three directions are independent of each other:

[0084] In the formula, For the flexural deformation angle, The angular velocity of the flexural deformation. The elastic coefficient of the deformable structure of the carrier. It is Gaussian white noise.

[0085] Considering the flexural deformation, the main and secondary inertial guide arms can be represented as:

[0086] In the formula, For the flexural deformation angle, These are the initial value of the lever arm and the value of the lever arm after considering flexural deformation, respectively. The coefficient matrix, .

[0087] The formula for calculating the state matrix is ​​as follows:

[0088] in,

[0089] , , , , , .

[0090] in, This is the Earth's rotational angular velocity. denotes the attitude misalignment angle, are the velocities in the east, north, and up directions, is the prime meridian radius of curvature, is the radius of curvature of the prime vertical, is the altitude, is the latitude, is the specific force, is the attitude matrix, is the elastic coefficient of the carrier deformation structure.

[0091] The state matrix is updated after each navigation calculation.

[0092] Judge whether it has reached the filtering time. If so, calculate the Kalman filter measurement and measurement matrix using the main inertial navigation information and navigation solution results received at the current time. The measurements selected for the fine alignment Kalman filter are:

[0093] The measurement calculation formula is as follows:

[0094] where represent the velocities of the slave and main inertial navigations respectively, represent the attitudes of the slave and main inertial navigations respectively.

[0095] The measurement matrix calculation formula is as follows:

[0096] where, , is the base attitude matrix of the slave inertial navigation, is the angular velocity of the carrier motion, is the platform attitude matrix of the slave inertial navigation, is the identity matrix.

[0097] Update the Kalman filter equation and calculate the estimated value of the state quantity.

[0098] (7) Estimation error compensation and correction. Calculate the alignment result and judge whether it has reached the alignment end time. If not, use the estimated velocity of the Kalman filter, the installation errors of the main and slave inertial navigations, and the flexure deformation angle to perform feedback correction on the system. The calculation formula is as follows: ,

[0099] where, is the estimated value of the state quantity, is the attitude error compensation matrix of the main and slave inertial navigations, is the estimated value of the installation errors of the main and slave inertial navigations, is the estimated value of the flexure deformation angle.

[0100] If the alignment completion time is reached, the alignment is terminated. The attitude misalignment angle estimated by the Kalman filter is used to compensate and correct the navigation results of the platform. The composite inertial navigation transfer alignment result is calculated using the following formula: Based on the fine alignment navigation calculation results, the attitude matrix of the composite inertial navigation platform at the alignment completion time is obtained as follows: The method for calculating the misalignment angle attitude compensation matrix based on the precise alignment Kalman filter estimation is as follows:

[0101] in, , represent the estimated attitude misalignment angles in the x, y, and z directions, respectively; the calculation formula for the transferred alignment result is obtained from the platform attitude matrix and the misalignment angle compensation matrix as follows:

[0102] in, To compensate for the background body pose matrix, i.e. to transmit the alignment result.

[0103] The above description is only the best specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the protection scope of the present invention.

[0104] The contents not described in detail in this specification are common knowledge to those skilled in the art.

Claims

1. A method for rapid and high-precision transfer alignment of a composite inertial system, characterized in that, include: S1. Construct a transfer alignment test control system using a main inertial navigation system and a composite inertial system that outputs speed and attitude information. Power on and heat the transfer alignment test control system, initialize its parameters, and control the rotating mechanism of the composite inertial system to rotate to the zero position to enter the transfer alignment process. S2. Calculate the interference angular motion information of the platform based on the gyroscope output signal of the composite inertial system, and then apply a corresponding control torque to the rotating mechanism to isolate the platform from external interference angular motion along the corresponding axis. S3. Apply control commands to the rotating mechanism, control the platform to rotate and stop along a predetermined rotation path, and simultaneously control the carrier to follow the specified direction. S4. Perform maneuvering and swaying under fixed angle motion conditions; S5. Real-time acquisition of gyroscope, accelerometer, and frame angle data signals of the composite inertial system, as well as synchronization signals, velocity, and attitude signals of the main inertial navigation system, and align the measurement data of the composite inertial system with the data of the main inertial navigation system based on the synchronization signals; S6. Perform coarse alignment using the inertial measurement data of the composite inertial system to obtain the initial attitude matrix of the platform relative to the navigation coordinate system; S7. Establish the initial attitude reference using the coarse alignment results, determine whether the navigation calculation time has been reached, and if so, perform navigation calculation using the inertial measurement data, while updating the state matrix of the fine alignment Kalman filter in real time; S7. Determine whether the filtering time has been reached. If it has, use the main inertial navigation velocity and attitude information received at the current time, after dynamic error compensation, to match it with the navigation solution of the composite inertial navigation system, calculate the precise alignment Kalman filter observation and observation matrix, update the Kalman filter equation, and calculate the state quantity estimate. S8. Determine whether the alignment end time has been reached. If not, use the Kalman filter to estimate the velocity error, the main inertial navigation system installation error, and the deflection angle to perform real-time feedback correction on the composite inertial navigation system. If so, the alignment is terminated, and the attitude misalignment angle estimated by the Kalman filter is used to compensate and correct the navigation results of the platform, thus obtaining the alignment results of the composite inertial system.

2. The rapid and high-precision transfer alignment method for a composite inertial system according to claim 1, characterized in that, In step S2, the open-loop transfer function of the control loop that isolates the platform from external disturbance angular motion along the corresponding axis is: in, Let the moment of inertia of the rotating mechanism's shaft be _____. This refers to the transfer function of the fiber optic gyroscope. For loop correction network, This is the power stage amplification factor. For the shaft-end torque motor transfer function, This represents the gain coefficient of the fiber optic gyroscope. This is the gain coefficient of the torque motor. is the time constant of the torque motor.

3. The rapid and high-precision transfer alignment method for a composite inertial system according to claim 1, characterized in that, In step S3, the rotation path includes two dwelling positions and two rotation processes. First, the platform is locked to the frame at a 180° position around the outer ring axis. After rotating to the position, the platform is in an isolation angle motion state and stays there for a period of time. Then, it rotates 180° clockwise around the outer ring axis to the frame at position 0 and stays there for a period of time. At the same time, the carrier is controlled to swing around the horizontal direction.

4. The rapid and high-precision transfer alignment method for a composite inertial system according to claim 1, characterized in that, In step S4, the gyroscope, accelerometer, and frame angle data signals of the composite inertial system and the synchronization signal, velocity, and attitude signals of the main inertial navigation system are acquired in real time. The measurement data of the composite inertial system is aligned with the data of the main inertial navigation system according to the synchronization signal. This includes: the composite inertial navigation system acquires the periodic square wave signal output by the main inertial navigation system. When the alignment process begins, the first falling edge of the synchronization signal received by the composite inertial navigation system is defined as the start time. The inertial measurement data received at this time is aligned with the velocity and attitude data of the main inertial navigation system. Data alignment is performed once at each subsequent falling edge.

5. The rapid and high-precision transfer alignment method for a composite inertial system according to claim 1, characterized in that, In step S5, coarse alignment is performed using inertial measurement data from the composite inertial system to obtain the initial attitude matrix of the platform relative to the navigation coordinate system. This includes: calculating a relatively accurate initial attitude information using a multi-vector attitude determination analytical coarse alignment method. The solution method is as follows: calculating the platform system velocity vector and the navigation system velocity vector. Value: in, and Let represent velocity and velocity increment respectively, T represent sampling period, subscript i represent the i-th sampling time, and superscript g represent projection in the navigation system; The number of samples, for The transformation matrix from the time-stage system to the solidification stage system. For angular increments, for The transformation matrix from the time-based navigation frame to the solidified navigation frame. For navigation system speed, For a moment, As a unit array, The projection of the rotational angular velocity of the navigation frame relative to the inertial frame onto the navigation frame. The projection of gravitational acceleration onto the navigation system. Project the Earth's rotational angular velocity onto the navigation frame; calculate the values ​​at multiple moments. According to the relation The least squares method was used to fit the data. The result is that the initial attitude matrix of the platform relative to the navigation coordinate system is solved as follows: in, The attitude transfer matrix from the solidification stage to the solidification stage; Let be the attitude transition matrix from the fixed navigation frame to the initial navigation frame; Let be the attitude transition matrix from the initial navigation frame to the current navigation frame. Let be the attitude transfer matrix from the solidified stage system to the solidified navigation system.

6. The rapid and high-precision transfer alignment method for a composite inertial system according to claim 1, characterized in that, In step S6, the state equation of the precisely aligned Kalman filter is: in, These are the state variables and their derivatives, respectively. The state matrix; For system noise; the formula for updating the state matrix of the precisely aligned Kalman filter is: in, This is a one-step prediction of the state at time k. Here is the filter state transition matrix. This is an estimate of the state at time k-1. The variance matrix for one-step prediction. For the estimated variance matrix, This is the system noise driving matrix.

7. The rapid and high-precision transfer alignment method for a composite inertial system according to claim 1, characterized in that, In step S7, the dynamic error compensation uses a second-order Gaussian-Markov process to describe the flexural motion, and the deformation processes in the three directions are independent of each other. The flexural deformation compensation model is as follows: in, It is Gaussian white noise with variance of ； The angular velocity of the flexural deformation; The elastic coefficient of the deformable structure of the carrier; Let be the deflection angle, and let be the root mean square. ,satisfy Dynamic lever effect error Represented as: in, Main and secondary inertial guide arms, The angular velocity of the carrier relative to the inertial frame of reference. For time. The dynamic installation error compensation model is as follows: in, The main inertial navigation system installation error angle For dynamic flexural deformation angle, For the installation error matrix, The identity matrix is ​​used; the observation equation for the precisely aligned Kalman filter is: in, For state variables, For observation purposes, For the observation matrix, To observe noise; the formula for calculating the measurement update of the precise aligned Kalman filter is: in, This is the optimal estimate of the state at time k. This is a one-step prediction of the state at time k. Here is the filter gain matrix. For observation purposes, For the observation matrix, The variance matrix for one-step prediction. To measure the noise variance matrix, The variance matrix is ​​the optimal estimate. It is a unit array.

8. The rapid and high-precision transfer alignment method for a composite inertial system according to claim 1, characterized in that, In step S8, the composite inertial system is corrected by using a Kalman filter to estimate the velocity error, the main inertial navigation system installation error, and the deflection angle. The velocity correction formula is as follows: in, This represents the velocity before and after Kalman filter feedback compensation at time k; These are the estimated velocity errors in the three directions of the navigation coordinate system; the attitude correction formula is: in, To compensate for the attitude error matrix from the sub-inertial navigation system to the main inertial navigation system, The initial values ​​of the attitude error matrix from the sub-inertial navigation system to the main inertial navigation system are given. The attitude error compensation matrix for the master and sub-inertial navigation systems; in, These represent the estimated installation error angles of the main and sub-inertial navigation systems in the x, y, and z directions, respectively. These represent the estimated values ​​of the flexural deformation angles in the x, y, and z directions, respectively.

9. The rapid and high-precision transfer alignment method for a composite inertial system according to claim 8, characterized in that, In step S8, the attitude misalignment angle estimated by the Kalman filter is used to compensate and correct the navigation results of the platform, resulting in the alignment result of the composite inertial system. This includes obtaining the platform attitude matrix at the end of the alignment based on the fine alignment navigation calculation results. The calculation method for the sub-INS attitude misalignment angle compensation matrix based on the precisely aligned Kalman filter estimation value is as follows: in, Let x, y, and z represent the estimated values ​​of the sub-inertial navigation attitude misalignment angles, respectively. The calculation method for the transferred alignment result, based on the platform attitude matrix and the misalignment angle compensation matrix, is as follows: in, To compensate for the background body pose matrix, i.e. to transmit the alignment result.

10. A composite inertial system rapid and high-precision transfer alignment device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 9.

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