Underwater micro inertial navigation wide-angle installation error transfer alignment method and device

Abstract

The invention relates to the technical field of inertial navigation guidance systems, and discloses an underwater micro inertial navigation wide-angle installation error transfer alignment method and device, and the method comprises the following steps: obtaining navigation information of a main inertial navigation, and calculating through an inversion algorithm to obtain simulation data of a main inertial navigation gyroscope and simulation data of an accelerometer; receiving gyroscope measurement data and accelerometer measurement data output by the micro inertial navigation, and constructing a transfer alignment target function taking the installation error as a variable by combining the simulation data of the main inertial navigation gyroscope and the simulation data of the accelerometer; and optimizing the transfer alignment target function by adopting an optimization algorithm to obtain an estimated value of the installation error so as to determine the installation error between the micro inertial navigation system and the high-precision inertial navigation system. The method does not depend on specific platform maneuvering, is high in calculation efficiency and robustness, and can realize rapid and accurate alignment of large installation errors.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of inertial navigation guidance, in particular to a method and device for transferring and aligning large-angle installation error of underwater micro-inertial navigation. BACKGROUND

[0002] Ocean exploration is of great significance for scientific research, resource exploration and utilization. Underwater robots have the advantages of small size, flexibility and other advantages, and can be released by the main platform underwater to complete the corresponding task. Considering that the conventional acoustic positioning system, global navigation satellite system and other hardware condition limitations cannot be used globally, the micro-electromechanical inertial navigation system, i.e. micro-inertial navigation, is concerned by the underwater robot field due to its small size, low cost and continuous navigation information, autonomy, high reliability and other advantages.

[0003] However, due to installation condition limitations and environmental condition changes, the underwater robot will have unknown attitude relative motion relative to the underwater main platform before release, resulting in unknown installation misalignment angle between the underwater robot micro-inertial navigation and the high-precision inertial navigation of the underwater main platform, which cannot complete the subsequent reliable autonomous navigation and positioning. The transfer alignment method based on nonlinear filtering or conventional optimization algorithm usually needs specific underwater platform maneuvering mode or huge calculation amount, which is difficult to be directly applied in engineering.

[0004] Therefore, the market urgently needs a large-angle installation error transfer alignment method and device for underwater platform micro-inertial navigation, which realizes the rapid and accurate transfer alignment of unknown large installation error of micro-inertial navigation. SUMMARY

[0005] The present application aims to at least solve one of the technical problems in the related art. To this end, the present application provides a large-angle installation error transfer alignment method and device for underwater micro-inertial navigation.

[0006] According to the embodiment of the present application, the first scheme is provided: A large-angle installation error transfer alignment method for underwater micro-inertial navigation, comprising the following steps: S1, receiving the navigation information output by the high-precision inertial navigation system of the main platform, and calculating the analog data of the main inertial navigation gyroscope and the analog data of the main inertial navigation accelerometer through inversion algorithm, the navigation information including attitude, velocity and position information; S2, receiving the gyroscope measurement data and accelerometer measurement data output by the micro-inertial navigation, and combining the analog data of the main inertial navigation gyroscope and the analog data of the main inertial navigation accelerometer obtained in S1 to construct a transfer alignment target function with the installation error of the micro-inertial navigation relative to the high-precision inertial navigation system as a variable; S3, an optimization algorithm is used to optimize the transfer alignment target function to obtain an estimated value of the installation error, so as to determine the installation error between the micro inertial navigation system and the high-precision inertial navigation system; In S2, the transfer alignment target function is constructed as: In the formula: is the gyro measurement value of the micro inertial navigation system of the sub-platform at i moment; is the accelerometer measurement value of the micro inertial navigation system of the sub-platform at i moment; is the simulation value of the accelerometer of the main inertial navigation system at i moment; is the simulation value of the gyro of the main inertial navigation system at i moment; is the true result of the installation error matrix, which is the installation error matrix formed by the installation error of the heading angle , the installation error of the pitch angle and the installation error of the roll angle ; is the estimated result of the installation error matrix obtained by transfer alignment; is the norm of the vector ; k represents the moment k.

[0007] Further, the transfer alignment target function equivalent function is constructed based on the transfer alignment target function, and only the influence of the diagonal elements of the installation error matrix on the transfer alignment target function equivalent function is considered. The form of the transfer alignment target function equivalent function is: In the formula: is the estimated result of the installation error matrix obtained by transfer alignment; is an information matrix constructed by using the gyro and accelerometer measurement results of the micro inertial navigation system and the simulation data of the gyro and accelerometer of the main inertial navigation system; is the sum of the diagonal elements of the matrix .

[0008] Further, at the moment k, the information matrix is represented as: In the formula, is the analog value of the master inertial navigation gyroscope at time i; is the gyroscope measurement value of the sub-platform micro inertial navigation at time i; is the analog value of the master inertial navigation accelerometer at time i; is the accelerometer measurement value of the sub-platform micro inertial navigation at time i.

[0009] Further, in S1, when calculating the analog data of the master inertial navigation accelerometer by the inversion algorithm, the oar error is compensated.

[0010] Further, in S1, when calculating the analog data of the master inertial navigation gyroscope by the inversion algorithm, the equivalent rotation vector error is compensated.

[0011] Further, in S3, the optimization algorithm is an intelligent optimization algorithm; and the intelligent optimization algorithm is a seagull optimization algorithm.

[0012] Further, the step of searching for optimization by using the seagull optimization algorithm comprises: initializing a seagull population in a three-dimensional search space constituted by the installation errors, and repeatedly performing migration movement and spiral attack within a preset number of iterations to search for a global optimal solution of the transfer alignment target function.

[0013] According to the embodiment of the present application, the first scheme provided by the present application is applied to the large-angle installation error transfer alignment method of the underwater platform micro inertial navigation, and the second scheme is provided: A computer device comprises a memory and a processor, the memory stores a computer program, and the computer program is executed by the processor to make the processor execute the following steps: S1, receiving navigation information output by a high-precision inertial navigation system of a master platform, and calculating analog data of a master inertial navigation gyroscope and analog data of a master inertial navigation accelerometer of the high-precision inertial navigation system by an inversion algorithm, the navigation information comprising attitude, speed and position information; S2, receiving gyroscope measurement data and accelerometer measurement data output by a micro inertial navigation, and combining the analog data of the master inertial navigation gyroscope and the analog data of the master inertial navigation accelerometer obtained in S1 to construct a transfer alignment target function taking installation errors of the micro inertial navigation relative to the high-precision inertial navigation system as variables; S3, searching for optimization of the transfer alignment target function by an optimization algorithm to obtain an estimated value of the installation errors, so as to determine the installation errors between the micro inertial navigation and the high-precision inertial navigation system; In S2, the transfer alignment target function is constructed as: In the formula, is the gyroscope measurement value of the sub-platform micro-inertial navigation at time i; is the accelerometer measurement value of the sub-platform micro-inertial navigation at time i; is the analog value of the main inertial navigation accelerometer at time i; is the analog value of the main inertial navigation gyroscope at time i; is the installation error matrix true result, the installation error matrix composed of the installation error between the main inertial navigation and the sub-inertial navigation, represented by the heading angle installation error , the pitch angle installation error and the roll angle installation error ; is the installation error matrix estimation result obtained by transfer alignment; is the norm of the vector ; k represents time k.

[0014] A computer readable storage medium stores a computer program, when the computer program is executed by a processor, the processor executes the following steps: S1, receiving navigation information output by a main platform high-precision inertial navigation system, and calculating analog data of a main inertial navigation gyroscope and analog data of a main inertial navigation accelerometer of the high-precision inertial navigation system through an inversion algorithm, the navigation information including attitude, speed and position information; S2, receiving gyroscope measurement data and accelerometer measurement data output by a micro-inertial navigation, and combining the analog data of the main inertial navigation gyroscope and the analog data of the main inertial navigation accelerometer obtained in S1, to construct a transfer alignment target function with installation error of the micro-inertial navigation relative to the high-precision inertial navigation system as a variable; S3, using an optimization algorithm to optimize the transfer alignment target function, to obtain an estimation value of the installation error, so as to determine the installation error between the micro-inertial navigation and the high-precision inertial navigation system; In S2, the transfer alignment target function is constructed as: In the formula: is the gyroscope measurement value of the sub-platform micro-inertial navigation at time i; is the accelerometer measurement value of the sub-platform micro-inertial navigation at time i; is the analog value of the main inertial navigation accelerometer at time i; is the simulation value of the main inertial navigation gyroscope at time i; is the installation error matrix real result, the installation error matrix formed by the installation error between the main inertial navigation and the sub-inertial navigation, the heading angle installation error , the pitch angle installation error and the roll angle installation error are represented; is the installation error matrix estimation result obtained by the transfer alignment; is the norm of the vector ; and k represents time k.

[0015] The one or more technical solutions in the embodiments of the present application have at least one of the following technical effects: 1. High precision and strong robustness: By constructing a target function matched with the angular velocity and specific force, and using an intelligent optimization algorithm with global search capability, the alignment problem of large angle installation error can be effectively solved. The numerical simulation experiment results show that even in the extreme large misalignment angle case with a heading installation error of up to 56°, the method can still achieve accurate and stable estimation, showing strong robustness and overcoming the defect that the traditional linearization method is easy to diverge at large angles.

[0016] 2. High computational efficiency: The core innovation of the present application is to transform the complex alignment problem into a scalar target function optimization problem with high computational efficiency. In particular, by constructing an information matrix and using the mathematical form of trace operation, the data processing process (low complexity accumulation) and the optimization solving process are ingeniously separated, and the calculation of single function value in optimization iteration is greatly simplified. This avoids the complex matrix inversion and high-dimensional covariance propagation operation involved in the traditional nonlinear filtering method, significantly reduces the requirement for the computing power of the navigation computer, and makes it more suitable for deployment on resource-limited underwater platforms.

[0017] 3. Strong engineering applicability: The method has excellent engineering adaptability. First, it does not depend on the main platform to perform any specific maneuver, and in theory, any dynamic change can provide effective information excitation for the construction of the information matrix. Second, through data inversion technology, the problem of not being able to directly obtain the original measurement data of the main inertial navigation, which is commonly encountered in engineering practice, is successfully solved, so that the method can be easily integrated and applied to various combinations of main and sub-platform systems, and has good versatility and portability.

[0018] 4. The overall scheme is fast and efficient: the entire alignment process is divided into two stages of data acquisition and optimization solution. The data acquisition stage can be completed in a short time (simulation is set to 60 seconds). And in the optimization solution stage, meta-heuristic optimization algorithm is adopted, which can quickly converge to the global optimal solution within a reasonable number of iterations. This "short-time acquisition, fast solution" feature can meet the urgent time efficiency requirements of the underwater robot to complete the initial alignment quickly before the task execution (such as before being released from the mother ship).

[0019] Additional aspects and advantages of the application will be set forth in part in the description which follows, and in part will become apparent to those having ordinary skill in the art upon examination of the following or can be learned from practice of the application. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are some embodiments of the application, and those skilled in the art can obtain other drawings according to these drawings without any creative effort.

[0021] Figure 1 is a device diagram for realizing the method for transferring and aligning large-angle installation errors of underwater micro-inertial navigation in the application; Figure 2 is a flowchart of the method for transferring and aligning large-angle installation errors of underwater micro-inertial navigation in the application; Figure 3 is a transfer and alignment result of the heading installation error in the application; Figure 4 is a transfer and alignment result of the pitch installation error in the application; Figure 5 is a transfer and alignment result of the roll installation error in the application; Figure 6 is a structural block diagram of the computer device in the application. DETAILED DESCRIPTION

[0022] In order to make the objectives, technical solutions and advantages of the application clearer, the technical solutions in the application will be clearly and completely described below. Obviously, the described embodiments are part of the embodiments of the application, rather than all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without any creative effort belong to the protection scope of the application. The following embodiments are used to illustrate the application, but cannot be used to limit the scope of the application.

[0023] The application focuses on a key technical pain point in the field of underwater robot navigation. Before being released by the mother ship (main platform), due to the limitations of installation conditions, structural flexural deformation and the influence of complex marine environment, the micro-electromechanical inertial navigation system (micro-inertial navigation, or sub-inertial navigation) carried by the underwater robot (sub-platform) and the high-precision inertial navigation system (main-inertial navigation) carried by the main platform often have an unknown and possibly large installation misalignment angle. If this misalignment angle cannot be accurately and quickly measured and compensated, it will directly lead to the underwater robot being unable to perform reliable autonomous navigation and positioning after leaving the mother ship, seriously affecting its mission execution capability.

[0024] In the prior art, the transfer alignment method based on nonlinear filtering (such as extended Kalman filter EKF, unscented Kalman filter UKF) or conventional optimization algorithm has significant engineering application limitations in dealing with this problem. For example, some methods require the main platform to perform specific maneuvering actions (such as turning, accelerating and decelerating) to ensure the observability of the misalignment angle, which is difficult to meet in actual tasks; another part of the method involves complex matrix operations and iterative processes, resulting in a huge amount of calculation, which poses a severe challenge to the limited computing resources of the underwater robot, making it difficult to achieve rapid alignment. Therefore, there is an urgent need in the market for a new transfer alignment method that does not rely on specific maneuvers, is computationally efficient and can accurately estimate large misalignment angles.

[0025] The application proposes a large-angle installation error transfer alignment method and device applied to the micro-inertial navigation of underwater platforms, which uses the gyroscope and accelerometer measurement data of the high-precision inertial navigation system (main-inertial navigation) of the main platform and the micro-inertial navigation system (sub-inertial navigation) of the underwater robot to construct a transfer alignment target function, and completes the transfer alignment of the unknown large installation error based on the albatross optimization algorithm. The device required for the transfer alignment process is shown in Figure 1 , wherein the main platform includes a high-precision inertial navigation system and a data sending device, and the underwater robot (sub-platform) includes a micro-inertial navigation system and a navigation computer.

[0026] The flowchart of the large-angle installation error transfer alignment method for underwater micro-inertial navigation proposed by the application is shown in Figure 2 .

[0027] The specific implementation of the application can be divided into three main steps.

[0028] The first step is that the sub-platform navigation computer receives the attitude, velocity and position information sent by the main-inertial navigation system, and obtains the simulation data of the gyroscope and accelerometer of the main-inertial navigation system through the inversion algorithm.

[0029] The application considers using the matching mode of "angular velocity + specific force" in the large-angle installation error transfer alignment, and the matching mode directly uses the measurement data of the gyroscope and the accelerometer to carry out alignment, and has good transfer alignment rapidity.

[0030] Due to the limitations of the high-precision inertial navigation mode and data communication protocol of the main platform, the gyroscope and accelerometer measurement information of the main inertial navigation is usually difficult to be directly obtained by the sub-platform, and in most cases, only the navigation information such as the attitude, velocity and position of the main platform is available. Therefore, the gyroscope and accelerometer data of the main inertial navigation need to be obtained by using the navigation information of the high-precision inertial navigation of the main platform. The navigation information of the high-precision inertial navigation of the main platform is sent to the sub-platform navigation computer through a data sending device, and the sub-platform navigation computer records the relevant information and calculates the analog data of the gyroscope and accelerometer of the main inertial navigation in the main platform.

[0031] The analog data of the gyroscope is obtained by using the navigation information of the main inertial navigation. Considering the compensation of the equivalent rotation vector error, the attitude update formula of the main inertial navigation at time k is represented as: …………………(1) In the formula, is the attitude matrix at time k, which is obtained from the attitude information of the main inertial navigation; is the navigation system rotation angular velocity caused by the earth rotation at time k-1 and the navigation system rotation angular velocity caused by the motion of the main inertial navigation , which can be obtained from the velocity and position information of the main inertial navigation; is the update period of the navigation information of the main inertial navigation; is the rotation vector of the main inertial navigation gyroscope analog value at time k; is the rotation vector of the main inertial navigation gyroscope analog value at time k-1 is converted into a matrix form, and the transpose of the matrix is represented as .

[0032] Processing formula (1) can obtain the rotation vector in the matrix form: …………………(2) Data extraction is performed on the left side of formula (2) to obtain the rotation vector of the main inertial navigation gyroscope analog value . The relationship between the rotation vector and the gyroscope analog value is usually represented as: …………………(3) In the formula: The analog value of the master inertial navigation gyroscope at time k.

[0033] Processing formula (3) can obtain the analog data of the master inertial navigation gyroscope: ……………………(4) In the formula: Unit matrix; The skew-symmetric matrix of vector .

[0034] The analog data of the master inertial navigation gyroscope can be obtained in real time through formula (2) and formula (4).

[0035] The analog data of the accelerometer is inversed by using the navigation information of the master inertial navigation. Considering the compensation of the rudder error, the velocity update formula of the master inertial navigation at time k is represented as: …………………………(5) …(6) ……………(7) In the formula: The velocity information of the master inertial navigation at time k; The analog value of the master inertial navigation accelerometer at time k; The earth gravity vector at time k-1; The skew-symmetric matrix of vector ; The specific force velocity increment at time k; The velocity increment corresponding to the harmful acceleration at time k; The earth rotation angular velocity at time k-1; The angular velocity of the carrier due to the movement relative to the earth surface at time k-1; The sum of the above two angular velocities at time k-1, that is, .

[0036] From formula (5) and formula (7), it can be obtained that is ……………(8) Substitute formula (8) into formula (6), the analog data of the master inertial navigation accelerometer can be obtained: …(9) The analog data of the master inertial navigation accelerometer can be obtained in real time through formula (8) and formula (9).

[0037] Secondly, the micro inertial navigation computer receives the micro inertial navigation gyroscope and accelerometer data, and combines the master inertial navigation gyroscope and accelerometer analog data to construct a transfer alignment target function.

[0038] Generally, the master inertial navigation precision of the underwater platform is higher than that of the sub-platform by more than several orders of magnitude, so the master inertial navigation error can be ignored. Since the installation angle between the sub-platform and the underwater master platform is unknown, and is affected by factors such as deflection deformation and lever arm, the micro inertial navigation of the sub-platform has unknown large installation errors. The measurement results of the gyroscope and accelerometer of the master inertial navigation and the micro inertial navigation of the sub-platform should approximately have the following relationship: …………………………………(10) …………………………………(11) In the formula: —gyroscope measurement value of the micro inertial navigation of the sub-platform at time k; —accelerometer measurement value of the micro inertial navigation of the sub-platform at time k; —installation error matrix composed of the installation errors between the master inertial navigation and the micro inertial navigation of the sub-platform, which is represented by the heading angle installation error , the pitch angle installation error and the roll angle installation error .

[0039] If there is an error between the installation error matrix estimation result obtained by transfer alignment and the true installation error matrix result , the gyroscope and accelerometer measurement results of the master inertial navigation and the micro inertial navigation of the sub-platform will have errors in the same coordinate system: …………………………(12) …………………………(13) In the formula: —error of the gyroscope measurement value of the micro inertial navigation of the sub-platform at time k and the gyroscope analog value of the master inertial navigation in the same coordinate system; —error of the accelerometer measurement value of the micro inertial navigation of the sub-platform at time k and the accelerometer analog value of the master inertial navigation in the same coordinate system.

[0040] The goal of this invention is to obtain the optimal installation error matrix estimation result , so that the errors of Equations (12) and (13) are minimized. It should be noted that Equations (12) and (13) show that the calculation accuracy of the installation error matrix simultaneously affects the gyro measurement error and accelerometer measurement error between the main inertial navigation system and the sub-platform micro-inertial navigation system in the same coordinate system. Moreover, Equations (12) and (13) are in vector form and cannot be directly compared. Therefore, it is necessary to convert the above error vector into scalar form.

[0041] Considering that the error vector expressed by equations (12) and (13) changes with time Change, optimal installation error matrix The error at any moment should be minimized. Therefore, when constructing the transfer alignment objective function, the impact of historical data on the objective function must be considered from the perspective of time series. In addition, the objective function must also consider the impact of the installation error matrix on the gyroscope and accelerometer measurement results. Based on the above considerations, the transfer alignment objective function proposed in this invention at time k is constructed as follows: ……………(14) Where: ——Vector The norm of .

[0042] If there exists an optimal estimation result of the installation error matrix , then the matrix should make the transfer alignment objective function (14) have the minimum value. In (14), the norm and Further expressed as: …………(15) …………(16) In formula (15) and formula (16), 、 is the measurement value of the sub-platform micro-inertial gyroscope and accelerometer, 、 The simulation data of the main inertial navigation gyro and accelerometer obtained in the first step of the present invention are all known quantities. Then, if the transfer alignment objective function expressed by formula (14) is There is a minimum value, which is equivalent to the following newly constructed k-time transfer alignment objective function equivalent function Should have maximum value: ……………(17) The installation error matrix in formula (17) Estimated value of installation error from heading angle , Estimated value of pitch angle installation error and the estimated value of roll angle installation error denotes: ……(18) where: — the sine value of , ; — the cosine value of .

[0043] Each element of the installation error matrix represented by the above formula has an unknown quantity to be solved , and If calculated according to formula (17), the calculation result of the transfer alignment target function equivalent function will be simultaneously affected by the 9 elements in the installation error matrix, and the form is complex. Therefore, only the diagonal elements of the installation error matrix are considered to affect the transfer alignment target function equivalent function .

[0044] Then, the transfer alignment target function equivalent function represented by formula (17) is further rewritten as: ……(19) where: — the sum of the diagonal elements of the matrix .

[0045] The transfer alignment target function equivalent function constructed according to formula (19) is used in the second step of the present application. The task of the sub-platform navigation computer is to simultaneously receive the micro-inertial gyro and accelerometer measurement results and the analog data of the main inertial gyro and accelerometer, perform accumulation operation and construct the transfer alignment target function equivalent function: ………………………………(20) where: — the information matrix constructed by using the micro-inertial gyro and accelerometer measurement results and the analog data of the main inertial gyro and accelerometer.

[0046] At time k, the information matrix is represented as: ……………………(21) At this time, the task of the transfer alignment target function equivalent function is to make and The sum of the diagonal elements of the matrix obtained by multiplying has a maximum value in formula (21).

[0047] To summarize, the second step is to construct an equivalent function for the transfer alignment objective function using the simulated data from the main inertial navigation gyro and accelerometer and the measured data from the micro inertial navigation gyro and accelerometer obtained in the first step. When the second step reaches the set time, the third step is executed. The set time can be set as needed, typically N minutes, where N ranges from 1 to 60.

[0048] In the third step, the sub-platform navigation computer stops receiving data from the main inertial navigation and the sub-inertial navigation, and uses the Seagull optimization algorithm to optimize the equivalent function of the constructed transfer alignment objective function to obtain the estimated value of the installation error of the sub-platform micro-inertial navigation.

[0049] It should be noted that when optimizing the transfer-to-objective function equivalent to the objective function in Equation (20), there may be multiple different installation error estimates that lead to local maxima in the objective function, making the optimization of the transfer-to-objective function equivalent to the objective function a typical multi-modal optimization problem. Therefore, it is necessary to select a reasonable optimization algorithm to optimize the equivalent function of the objective function.

[0050] The Seagull Optimization Algorithm (SOA) draws inspiration from the migratory and aggression behaviors of seagulls in nature, providing a viable solution for optimizing the transfer-to-target objective function. Compared to other algorithms, the SOA's migratory movements enable a large-scale random search, avoiding local optima. Its spiraling attack, including trigonometric, exponential, and spiral equations, accelerates local search and improves the algorithm's convergence rate. Compared to other optimization algorithms, the SOA's unique optimization properties make it the preferred method for optimizing the transfer-to-target objective function, as multiple solutions to the objective function with local maxima exist.

[0051] The optimization process of the equivalent function of the transfer-aligned objective function based on the seagull optimization algorithm includes seagull population initialization, migration movement and spiral attack on prey.

[0052] In the initialization of the seagull population, the population needs to be distributed in the range of values ​​to be solved according to reasonable rules. For the unknown large installation error obtained by the transfer alignment in the present invention, the quantities to be solved include the heading angle installation error , Pitch angle installation error and roll angle installation error , which constitute a three-dimensional search space.

[0053] Population three-dimensional position The initialization is expressed as: ………………………(22) In the formula: - the population position vector corresponding to the installation error of the heading angle; - the population position vector corresponding to the installation error of the pitch angle; - the population position vector corresponding to the installation error of the roll angle; - the N-dimensional random number sequence vector, N representing the number of seagull populations, the random number taking a value greater than 0 and less than 1; 、 - the lower bound and the upper bound of the installation error value of the heading angle, wherein 、 ; 、 - the lower bound and the upper bound of the installation error value of the pitch angle, wherein 、 ; 、 - the lower bound and the upper bound of the installation error value of the roll angle, wherein 、 .

[0054] The fitness of the population at this time (i.e. the transmission alignment target function value) is calculated, and the best individual is obtained: ………………………(23) In the formula: - the fitness of the nth population; - the maximum fitness; - the installation error matrix expressed by the heading, pitch, and roll installation error angles corresponding to the nth seagull individual; - the position of the seagull individual with the maximum fitness.

[0055] Subsequently, the migration movement and attack of the seagull population will be completed within a given number of iterations of the algorithm according to the above initialization results.

[0056] In the migration movement, the movement of the seagull population in the search space should avoid mutual collision and approach the best individual.

[0057] If the maximum number of iterations is given , then in the tth iteration process, the migration movement direction of the seagull population is represented as: ……………………………(24) In the formula: Control parameters; Movement behavior of the seabirds in the search space; Random number balancing global search and local search; Migration direction of the seabirds.

[0058] In the spiral attack of the prey, the seabirds will perform three-dimensional spiral movement in the air to approach the prey target, and the behavior of the seabirds attacking the prey can be understood as updating towards the global optimal solution of the transfer alignment target function.

[0059] The spiral movement of the seabirds is expressed as: …………………………………(25) In the formula: Spiral movement radius; , Shape control parameter of the spiral movement; Attack angle random number, value range ; , , Coordinate of the spiral movement converted to the three-dimensional space.

[0060] Finally, the position update completed by the seabirds is expressed as: ……………………………(26) After completing the position update, the fitness of the updated population and the best individual are recalculated by using formula (23). In the iteration process, formula (24)-(26) are repeatedly executed until the maximum number of iterations is reached, and finally the best individual with the maximum fitness for the transfer alignment target function equivalent function is obtained , which includes the heading angle installation error estimation value , the pitch angle installation error estimation value , and the roll angle installation error estimation value .

[0061] In summary, according to the above installation error estimation values, the installation error matrix can be obtained, and the transfer alignment of the unknown large installation error is completed.

[0062] It should be noted that the present invention uses the Seagull optimization algorithm to optimize the constructed objective function to achieve transfer alignment of unknown large installation errors. The transfer alignment method implemented by using other intelligent optimization algorithms to calculate the objective function constructed in the present invention should also be within the scope of protection of the present invention.

[0063] In order to verify the effectiveness of the present invention, numerical simulation experiments were carried out. Considering that the underwater robot is fixed on the underwater main platform before release, the heading installation error angle between the underwater robot micro-inertial navigation and the underwater main platform high-precision inertial navigation is set to 56°, the pitch installation error angle is 0.4°, and the roll installation error angle is -0.3°. The gyro zero bias stability of the underwater robot micro-inertial navigation is 1° / h, and the accelerometer zero bias stability is 0.2mg. The maneuvers carried out by the underwater main platform include acceleration and turning. In the seagull optimization algorithm, the number of seagulls is set to 1000, the maximum number of iterations is set to 100, and the shape control parameters of the spiral motion are set to 0. and are all set to 1. The transfer alignment time is set to 60s, and the heading installation error estimation results obtained by the transfer alignment method proposed in this invention are as follows: Figure 3 As shown, the pitch installation error estimation results are as follows Figure 4 As shown in the figure, the roll installation error estimation results are as follows: Figure 5 The experimental results show that the method proposed in the present invention can realize the transfer alignment of large-angle installation errors of the underwater platform micro-inertial navigation.

[0064] like Figure 6 As shown, the computer device includes a processor, a memory, and a network interface connected via a system bus. The memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system and may also store a computer program. When the computer program is executed by the processor, the processor may implement a large-angle installation error transfer alignment method applied to underwater platform micro-inertial navigation. The internal memory may also store a computer program. When the computer program is executed by the processor, the processor may implement a large-angle installation error transfer alignment method applied to underwater platform micro-inertial navigation. Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0065] In one embodiment, a computer device is provided, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the following steps: S1, receiving navigation information output by a high-precision inertial navigation system of a main platform, and calculating analog data of a main inertial navigation gyroscope and an analog data of a main inertial navigation accelerometer of the high-precision inertial navigation system through an inversion algorithm, wherein the navigation information includes attitude, velocity, and position information; S2, receiving gyro measurement data and accelerometer measurement data output by the micro inertial navigation system, and combining the simulated data of the main inertial navigation gyro and the simulated data of the main inertial navigation accelerometer obtained in S1, to construct a transfer alignment objective function with an installation error of the micro inertial navigation system relative to the high-precision inertial navigation system as a variable; S3, optimizing the transfer alignment objective function using an optimization algorithm to obtain an estimated value of the installation error, so as to determine the installation error between the micro inertial navigation system and the high-precision inertial navigation system; In S2, the transfer alignment objective function is constructed as: Where: is the gyro measurement value of the sub-platform micro-inertial navigation at time i; is the accelerometer measurement value of the sub-platform micro-inertial navigation at time i; is the analog value of the main inertial navigation accelerometer at time i; is the analog value of the main inertial navigation gyro at time i; is the actual result of the installation error matrix, the installation error matrix composed of the installation error between the main inertial navigation and the sub-inertial navigation, which is composed of the heading angle installation error , Pitch angle installation error and roll angle installation error express; Estimation of the installation error matrix obtained for transfer alignment; For vector The norm of k represents the kth moment.

[0066] In one embodiment, a computer-readable storage medium is provided, storing a computer program. When the computer program is executed by a processor, the processor performs the following steps: S1, receiving navigation information output by a high-precision inertial navigation system of a main platform, and calculating analog data of a main inertial navigation gyroscope and an analog data of a main inertial navigation accelerometer of the high-precision inertial navigation system through an inversion algorithm, wherein the navigation information includes attitude, velocity, and position information; S2, receiving the gyro measurement data and the accelerometer measurement data of the micro inertial navigation output, and combining the analog data of the main inertial navigation gyro and the analog data of the main inertial navigation accelerometer obtained by S1, to construct a transfer alignment target function with the installation error of the micro inertial navigation relative to the high-precision inertial navigation system as a variable; S3, using an optimization algorithm to optimize the transfer alignment target function to obtain an estimated value of the installation error, so as to determine the installation error between the micro inertial navigation and the high-precision inertial navigation system; In S2, the transfer alignment target function is constructed as: In the formula: is the gyro measurement value of the micro inertial navigation of the sub-platform at i moment; is the accelerometer measurement value of the micro inertial navigation of the sub-platform at i moment; is the analog value of the main inertial navigation accelerometer at i moment; is the analog value of the main inertial navigation gyro at i moment; is the true result of the installation error matrix, which is the installation error matrix composed of the installation error of the main inertial navigation and the installation error of the micro inertial navigation, represented by the heading angle installation error , the pitch angle installation error and the roll angle installation error ; is the estimated result of the installation error matrix obtained by the transfer alignment; is the norm of the vector ; k represents the k moment.

[0067] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The program can be stored in a non-volatile computer readable storage medium, and when the program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, storage, database or other medium used in each embodiment provided by the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0068] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for error transfer and alignment of underwater micro-inertial navigation system with large angle installation, characterized in that: The following steps are involved: S1, receiving navigation information output by a high-precision inertial navigation system of a main platform, and calculating analog data of a main inertial navigation gyroscope and an analog data of a main inertial navigation accelerometer of the high-precision inertial navigation system through an inversion algorithm, wherein the navigation information includes attitude, velocity, and position information; S2, receiving gyro measurement data and accelerometer measurement data output by the micro inertial navigation system, and combining the simulated data of the main inertial navigation gyro and the simulated data of the main inertial navigation accelerometer obtained in S1, to construct a transfer alignment objective function with an installation error of the micro inertial navigation system relative to the high-precision inertial navigation system as a variable; S3, optimizing the transfer alignment objective function using an optimization algorithm to obtain an estimated value of the installation error, so as to determine the installation error between the micro inertial navigation system and the high-precision inertial navigation system; In S2, the transfer alignment objective function is constructed as: Where: is the gyro measurement value of the sub-platform micro-inertial navigation at time i; is the accelerometer measurement value of the sub-platform micro-inertial navigation at time i; is the analog value of the main inertial navigation accelerometer at time i; is the analog value of the main inertial navigation gyro at time i; is the actual result of the installation error matrix, the installation error matrix composed of the installation error between the main inertial navigation and the sub-inertial navigation, which is composed of the heading angle installation error , Pitch angle installation error and roll angle installation error express; Estimation of the installation error matrix obtained for transfer alignment; is a vector The norm of k represents the kth moment.

2. The error transfer and alignment method for large-angle installation of underwater micro-inertial navigation according to claim 1 is characterized in that: Based on the transfer alignment objective function, an equivalent function of the transfer alignment objective function is constructed and only the influence of the diagonal elements of the installation error matrix on the equivalent function of the transfer alignment objective function is considered; The equivalent function form of the transfer alignment objective function is: Where: Estimation of the installation error matrix obtained for transfer alignment; An information matrix constructed using the measurement results of the micro inertial navigation gyro and accelerometer and the simulated data of the main inertial navigation gyro and accelerometer; is a matrix The sum of the diagonal elements of .

3. The error transfer alignment method for large-angle installation of underwater micro-inertial navigation according to claim 2, characterized in that: At time k, the information matrix Expressed as: Where, is the analog value of the main inertial navigation gyro at time i; is the gyro measurement value of the sub-platform micro-inertial navigation at time i; is the analog value of the main inertial navigation accelerometer at time i; is the accelerometer measurement value of the sub-platform micro-inertial navigation at time i.

4. The error transfer alignment method for large-angle installation of underwater micro-inertial navigation according to claim 1 is characterized in that: In S1, the paddling error is compensated when the analog data of the main inertial navigation accelerometer is calculated by the inversion algorithm.

5. The error transfer and alignment method for large-angle installation of underwater micro-inertial navigation according to claim 1 is characterized in that: In S1, when the analog data of the main inertial navigation gyro is calculated by the inversion algorithm, the equivalent rotation vector error is compensated.

6. The error transfer alignment method for large-angle installation of underwater micro-inertial navigation according to claim 1, characterized in that: In S3, the optimization algorithm is an intelligent optimization algorithm; the intelligent optimization algorithm is a Seagull optimization algorithm.

7. The error transfer and alignment method for large-angle installation of underwater micro-inertial navigation according to claim 6, characterized in that: The steps of optimizing using the seagull optimization algorithm include: initializing a seagull population in a three-dimensional search space formed by the installation error, and repeatedly performing migration movement and spiral attack within a preset number of iterations to search for the global optimal solution of the transfer alignment objective function.

8. A computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor is caused to perform the steps of the method according to any one of claims 1 to 7.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor is caused to perform the steps of the method according to any one of claims 1 to 7.

Images