Method and device for underwater micro-inertial navigation large-angle installation error transfer alignment

Abstract

The application relates to the technical field of inertial navigation guiding systems, and discloses a method and device for transferring alignment of a large-angle installation error of an underwater micro inertial navigation system, which comprises the following steps: obtaining navigation information of a main inertial navigation system, and calculating analog data of a gyroscope and analog data of an accelerometer of the main inertial navigation system through an inversion algorithm; receiving gyroscope measurement data and accelerometer measurement data output by a micro inertial navigation system; combining the analog data of the gyroscope and the analog data of the accelerometer of the main inertial navigation system to construct a transfer alignment target function with installation error as a variable; and 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 system and the high-precision inertial navigation system. The application does not depend on specific platform maneuvering, has high calculation efficiency and strong robustness, and can realize rapid and accurate alignment of a large installation error.

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 can be released by the main platform underwater to complete the corresponding tasks. Considering that the conventional acoustic positioning system and global navigation satellite system have hardware condition limitations and cannot be used globally, 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, autonomous and highly reliable navigation information.

[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 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 as follows:

[0007] A large-angle installation error transfer alignment method for underwater micro-inertial navigation, comprising the following steps:

[0008] 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;

[0009] 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;

[0010] S3, optimizing the transfer alignment target function by 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;

[0011] In S2, the transfer alignment target function is constructed as:

[0012]

[0013] In the formula:

[0014] is the gyro measurement value of the micro inertial navigation system of the sub-platform at the i moment;

[0015] is the accelerometer measurement value of the micro inertial navigation system of the sub-platform at the i moment;

[0016] is the analog value of the accelerometer of the master inertial navigation system at the i moment;

[0017] is the analog value of the gyro of the master inertial navigation system at the i moment;

[0018] 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 ;

[0019] is the estimated result of the installation error matrix obtained by the transfer alignment;

[0020] is the norm of the vector ;

[0021] k represents the k moment.

[0022] 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.

[0023] The form of the transfer alignment target function equivalent function is:

[0024]

[0025] In the formula:

[0026] is the estimated result of the installation error matrix obtained by the transfer alignment;

[0027] an information matrix constructed by using the micro-inertial gyroscope and accelerometer measurement results and the simulation data of the main inertial gyroscope and accelerometer;

[0028] the sum of the diagonal elements of the matrix .

[0029] Further, at the k moment, the information matrix is expressed as:

[0030]

[0031] In the formula,

[0032] is the simulation value of the main inertial gyroscope at the i moment;

[0033] is the gyroscope measurement value of the micro-inertial platform at the i moment;

[0034] is the simulation value of the main inertial accelerometer at the i moment;

[0035] is the accelerometer measurement value of the micro-inertial platform at the i moment.

[0036] Further, in S1, when the simulation data of the main inertial accelerometer is calculated by the inversion algorithm, the oar error is compensated.

[0037] Further, in S1, when the simulation data of the main inertial gyroscope is calculated by the inversion algorithm, the equivalent rotation vector error is compensated.

[0038] Further, in S3, the optimization algorithm is an intelligent optimization algorithm; and the intelligent optimization algorithm is a seagull optimization algorithm.

[0039] 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.

[0040] 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 micro-inertial platform of the underwater platform, and the second scheme is provided as follows:

[0041] 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:

[0042] S1, receiving navigation information output by a high-precision inertial navigation system of a main platform, and calculating analog data of a main inertial gyro and analog data of a main inertial accelerometer of the high-precision inertial navigation system through an inversion algorithm, the navigation information including attitude, speed and position information;

[0043] S2, receiving gyro measurement data and accelerometer measurement data output by a micro inertial navigation system, and combining the analog data of the main inertial gyro and the analog data of the main inertial accelerometer obtained in S1 to construct a transfer alignment target function with installation errors of the micro inertial navigation system relative to the high-precision inertial navigation system as variables;

[0044] S3, using an optimization algorithm to optimize the transfer alignment target function to obtain an estimated value of the installation errors, so as to determine installation errors between the micro inertial navigation system and the high-precision inertial navigation system;

[0045] In S2, the transfer alignment target function is constructed as:

[0046]

[0047] In the formula:

[0048] is a gyro measurement value of a micro inertial navigation system of a sub platform at i moment;

[0049] is an accelerometer measurement value of the micro inertial navigation system of the sub platform at i moment;

[0050] is an analog value of a main inertial accelerometer at i moment;

[0051] is an analog value of a main inertial gyro at i moment;

[0052] is a true result of an installation error matrix, the installation error matrix being composed of installation errors between the main inertial navigation system and the micro inertial navigation system, the installation errors being represented by a heading angle installation error , a pitch angle installation error and a roll angle installation error ;

[0053] is an estimated result of the installation error matrix obtained by transfer alignment;

[0054] is a norm of a vector ;

[0055] k represents k moment.

[0056] A computer readable storage medium stores a computer program, the computer program is executed by a processor, so that the processor executes the following steps:

[0057] S1, receiving navigation information output by a main platform high-precision inertial navigation system, and calculating analog data of a main inertial gyro and analog data of a main inertial accelerometer of the high-precision inertial navigation system through an inversion algorithm, the navigation information including attitude, velocity and position information;

[0058] S2, receiving gyro measurement data and accelerometer measurement data output by a micro inertial navigation system, and combining the analog data of the main inertial gyro and the analog data of the main inertial accelerometer obtained in S1, a transfer alignment target function is constructed with installation errors of the micro inertial navigation system relative to the high-precision inertial navigation system as variables;

[0059] S3, an optimization algorithm is used to optimize the transfer alignment target function, and an estimated value of the installation error is obtained to determine the installation error between the micro inertial navigation system and the high-precision inertial navigation system;

[0060] In S2, the transfer alignment target function is constructed as:

[0061]

[0062] In the formula:

[0063] is a gyro measurement value of a micro inertial navigation system of a sub platform at i moment;

[0064] is an accelerometer measurement value of the micro inertial navigation system of the sub platform at i moment;

[0065] is an analog value of a main inertial accelerometer at i moment;

[0066] is an analog value of a main inertial gyro at i moment;

[0067] is a real result of an installation error matrix, the installation error matrix is formed by installation errors of a heading angle , an installation error of a pitch angle and an installation error of a roll angle ;

[0068] is an estimated result of the installation error matrix obtained by transfer alignment;

[0069] is a norm of a vector ;

[0070] k represents the k-th moment.

[0071] The one or more technical solutions in the embodiments of the present application have at least one of the following technical effects:

[0072] 1. High precision and strong robustness: By constructing a target function matched with "angular velocity + specific force", and using an intelligent optimization algorithm with global search capability, the alignment problem of large installation error can be effectively solved. Numerical simulation 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.

[0073] 2. High computational efficiency: The core innovation of the present application is to transform the complex alignment problem into a computationally efficient scalar target function optimization problem. 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 traditional nonlinear filtering methods, significantly reduces the computational power requirement of the navigation computer, and makes it more suitable for deployment on resource-constrained underwater platforms.

[0074] 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 incentive 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 system is successfully solved, making the method easy to integrate and apply to various combinations of main and sub-platform systems, with good versatility and portability.

[0075] 4. Fast and efficient overall scheme: The entire alignment process is divided into two stages: data acquisition and optimization solving. The data acquisition stage can be completed in a short time (set to 60 seconds in simulation). In the optimization solving stage, the meta-heuristic optimization algorithm can quickly converge to the global optimal solution within a reasonable number of iterations. This "short acquisition and fast solving" feature can meet the urgent time efficiency requirements of underwater robots to complete initial alignment before task execution (such as before release from the mother ship).

[0076] Additional aspects and advantages of the application will be in part apparent and in part pointed out hereinafter. BRIEF DESCRIPTION OF DRAWINGS

[0077] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings described below are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0078] Figure 1 It is a device diagram for realizing the method for transferring and aligning large-angle installation error of underwater micro-inertial navigation in the present application;

[0079] Figure 2 It is a flow chart of the method for transferring and aligning large-angle installation error of underwater micro-inertial navigation in the present application;

[0080] Figure 3 It is a transfer and alignment result of heading installation error in the present application;

[0081] Figure 4 It is a transfer and alignment result diagram of pitch installation error in the present application;

[0082] Figure 5 It is a transfer and alignment result diagram of roll installation error in the present application;

[0083] Figure 6 It is a structure block diagram of the computer device in the present application. DETAILED DESCRIPTION

[0084] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be clearly and completely described below. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor belong to the protection scope of the present application. The following embodiments are used to illustrate the present application, but cannot be used to limit the scope of the present application.

[0085] The present application focuses on a key technical pain point in the field of underwater robot navigation. Before being released by the mother ship (main platform), the micro-electromechanical inertial navigation system (micro-inertial navigation, or sub-inertial navigation) carried by the underwater robot (sub-platform) often has an unknown and possibly large-angle installation misalignment angle with the high-precision inertial navigation system (main-inertial navigation) carried by the main platform due to the limitations of installation conditions, structural flexural deformation and the influence of complex ocean environment. 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, and seriously affecting its mission execution capability.

[0086] 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 master 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 underwater robots, 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.

[0087] The present application proposes a large-angle installation error transfer alignment method and device applied to micro-inertial navigation of underwater platforms, which utilizes the gyro and accelerometer measurement data of the high-precision inertial navigation system (master inertial navigation) of the master 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 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 master platform includes a high-precision inertial navigation system and a data transmission device, and the underwater robot (sub-platform) includes a micro-inertial navigation system and a navigation computer.

[0088] The flowchart of the large-angle installation error transfer alignment method for underwater micro-inertial navigation proposed by the present application is shown in Figure 2 .

[0089] The specific implementation of the present application can be divided into three main steps.

[0090] First, the sub-platform navigation computer receives the attitude, velocity and position information sent by the master inertial navigation system, and obtains the analog data of the gyro and accelerometer of the master inertial navigation system through the inversion algorithm.

[0091] In the large-angle installation error transfer alignment, the present application considers using the "angular velocity + specific force" matching method, which directly uses the measurement data of the gyro and accelerometer to carry out alignment, and has good transfer alignment speed. The large-angle installation error transfer alignment method applied to micro-inertial navigation of underwater platforms proposed by the present application utilizes the measurement data of the gyro and accelerometer of the master inertial navigation system and the micro-inertial navigation system.

[0092] Due to the high-precision inertial navigation mode and data communication protocol of the master platform, the slave platform usually cannot directly obtain the gyro and accelerometer measurement information of the master inertial navigation system, and only has the navigation information such as the attitude, velocity and position of the master platform in most cases. Therefore, the gyro and accelerometer data of the master inertial navigation system need to be obtained by using the navigation information of the high-precision inertial navigation of the master platform. The navigation information of the high-precision inertial navigation of the master platform is sent to the slave platform navigation computer through a data sending device, and the slave platform navigation computer records the relevant information and calculates the analog data of the gyro and accelerometer of the master inertial navigation system in the master platform.

[0093] The analog data of the gyro is obtained by using the navigation information of the master inertial navigation system. Considering the compensation of the equivalent rotation vector error, the attitude update formula of the master inertial navigation system at time k is represented as:

[0094] (1)

[0095] In the formula,

[0096] Ck- attitude matrix at time k, obtained from the attitude information of the master inertial navigation system;

[0097] Ωk-1- navigation system rotation angular velocity caused by the earth rotation at time k-1 Ωk- navigation system rotation angular velocity caused by the motion of the master inertial navigation system at time k, which can be obtained from the velocity and position information of the master inertial navigation system;

[0098] Tk- update period of the navigation information of the master inertial navigation system;

[0099] Ωk- rotation vector of the gyro analog value of the master inertial navigation system at time k;

[0100] Rk- rotation matrix of the rotation vector Ωk . .

[0101] Processing formula (1) can obtain the rotation vector in the matrix form:

[0102] (2)

[0103] Data extraction can be performed on the left side of formula (2) to obtain the rotation vector Ωkof the gyro analog value of the master inertial navigation system. The relationship between the rotation vector and the gyro analog value is usually represented as:

[0104] (3)

[0105] In the formula,

[0106] - the analog value of the master inertial navigation gyroscope at time k.

[0107] Processing equation (3) can obtain the analog data of the master inertial navigation gyroscope:

[0108] …(4)

[0109] In the equation:

[0110] - unit matrix;

[0111] - the anti-symmetric matrix of vector .

[0112] The analog data of the master inertial navigation gyroscope can be obtained in real time through equation (2) and equation (4).

[0113] The analog data of the accelerometer is inversed 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 expressed as:

[0114] …(5)

[0115] …(6)

[0116] …(7)

[0117] In the equation:

[0118] - the velocity information of the master inertial navigation at time k;

[0119] - the analog value of the master inertial navigation accelerometer at time k;

[0120] - the earth gravity vector at time k-1;

[0121] - the anti-symmetric matrix of vector ;

[0122] - the specific force velocity increment at time k;

[0123] - the velocity increment corresponding to the harmful acceleration at time k;

[0124] - the earth rotation angular velocity at time k-1;

[0125] - the angular velocity of the carrier at time k-1 due to the motion relative to the earth surface;

[0126] - the sum of the above two angular velocities at time k-1, i.e. .

[0127] From equation (5) and equation (7), we can get = ωk-1+ ωk-1

[0128] ………(8)

[0129] Substitute equation (8) into equation (6), we can get the simulation data of the master inertial navigation accelerometer:

[0130] ……(9)

[0131] Through equation (8) and equation (9), we can get the simulation data of the master inertial navigation accelerometer in real time.

[0132] Secondly, the micro inertial navigation computer receives the micro inertial gyroscope and accelerometer data, and combines the master inertial gyroscope and accelerometer simulation data to construct the transfer alignment target function.

[0133] Generally, the master inertial navigation accuracy 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 flexural 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:

[0134] …………………………………(10)

[0135] …………………………………(11)

[0136] In the formula:

[0137] - the gyroscope measurement value of the micro inertial navigation of the sub-platform at time k;

[0138] - the accelerometer measurement value of the micro inertial navigation of the sub-platform at time k;

[0139] - the installation error matrix composed of the installation errors between the master inertial navigation and the micro inertial navigation, which is represented by the heading angle installation error , the pitch angle installation error and the roll angle installation error .

[0140] If the installation error matrix estimation result obtained from alignment is passed Compared with the actual results of the installation error matrix If errors exist between them, the gyroscope and accelerometer measurements from the main inertial navigation system and the sub-platform micro inertial navigation system will have errors in the same coordinate system:

[0141] …………………………(12)

[0142] …………………………(13)

[0143] In the formula:

[0144] —The error between the measured value of the sub-inertial gyroscope and the simulated value of the main inertial gyroscope at time k in the same coordinate system;

[0145] —The error between the sub-inertial accelerometer measurement and the main inertial accelerometer simulation at time k in the same coordinate system.

[0146] The objective of this invention is to obtain the optimal installation error matrix estimation result. This minimizes the errors in equations (12) and (13). It should be noted that equations (12) and (13) show that the calculation accuracy of the installation error matrix simultaneously affects the gyroscope 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. Furthermore, equations (12) and (13) are in vector form and cannot be directly compared in magnitude. Therefore, the aforementioned error vectors need to be converted into scalar form.

[0147] Considering that the error vector expressed by equations (12) and (13) varies with time... Variation, optimal installation error matrix To minimize the error at any given time, the transfer alignment objective function must be constructed by considering the impact of historical data on the objective function from a time series perspective. Furthermore, the objective function must simultaneously consider the influence of the installation error matrix on the gyroscope and accelerometer measurement results. Based on these considerations, the transfer alignment objective function at time k proposed in this invention is constructed as follows:

[0148] ……………(14)

[0149] In the formula:

[0150] — Vector The norm of .

[0151] If there exists an optimal estimation result for the installation error matrix. The matrix should make the transfer alignment objective function (14) have a minimum value. In equation (14), the norm and are further expressed as:

[0152] ……(15)

[0153] ……(16)

[0154] In equations (15) and (16), 、 are the measurement values of the micro-inertial gyroscopes and accelerometers of the sub-platform, 、 are the analog data of the main inertial gyroscopes and accelerometers obtained in the first step of the present application, and are known quantities. Then, if the transfer alignment objective function represented by equation (14) has a minimum value, it is equivalent to the newly constructed transfer alignment objective function equivalent function at time k should have a maximum value:

[0155] ……(17)

[0156] In equation (17), the installation error matrix is represented by the estimated value of the heading angle installation error , the estimated value of the pitch angle installation error , and the estimated value of the roll angle installation error :

[0157] ……(18)

[0158] In the equation:

[0159] the sine value of , ; ;

[0160] the cosine value of .

[0161] Each element of the installation error matrix represented by the above equation has an unknown quantity 、 and to be solved. If calculated according to equation (17), the calculation result of the transfer alignment objective 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 objective function equivalent function .​

[0162] Then, the transfer alignment target function equivalent function represented by formula (17) is Further rewritten as:

[0163] ………………(19)

[0164] In the formula:

[0165] The sum of the diagonal elements of the matrix

[0166] According to the transfer alignment target function equivalent function constructed by formula (19), 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, and to perform accumulation operation and construct the transfer alignment target function equivalent function:

[0167] ………………………………(20)

[0168] In the formula:

[0169] The information matrix constructed by the micro-inertial gyro and accelerometer measurement results and the analog data of the main inertial gyro and accelerometer.

[0170] At time k, the information matrix is expressed as:

[0171] ……………………(21)

[0172] At this time, the task of the transfer alignment target function equivalent function is to make The sum of the diagonal elements of the matrix obtained by the product of Formula (21) has the maximum value.

[0173] In summary, the second step is summarized as follows: using the analog data of the main inertial gyro and accelerometer obtained in the first step and the micro-inertial gyro and accelerometer measurement data to construct the transfer alignment target function equivalent function, and after the second step is executed for a set time, the third step is executed. The set time can be set as needed, usually N minutes, N is 1-60.

[0174] In the third step, the sub-platform navigation computer stops receiving the data of the main inertial navigation and the sub-inertial navigation, and uses the albatross optimization algorithm to optimize the constructed transfer alignment target function equivalent function to obtain the estimated value of the installation error of the sub-platform micro-inertial navigation.

[0175] ​It should be noted that in the process of optimizing the transfer alignment target function equivalent function of formula (20), there can be multiple different installation error estimation results to make the target function have a local maximum, so that the optimization problem of the transfer alignment target function equivalent function becomes a typical multi-peak optimization problem. Therefore, a reasonable optimization algorithm needs to be selected to optimize the target function equivalent function.

[0176] The Seagull Optimization Algorithm (SOA) draws on the migration and attack behavior of seagulls in nature, and provides a feasible solution for optimizing the transfer alignment target function. Compared with other algorithms, the migration movement of the Seagull Optimization Algorithm can realize large-scale random search and avoid falling into local optimal solution, while the spiral attack behavior includes trigonometric function, exponential function and spiral equation, which helps to accelerate local search and improve the convergence speed of the algorithm. Compared with other optimization algorithms, the Seagull Optimization Algorithm has the unique optimization characteristics of facing multiple different solutions of the transfer alignment target function, which makes it the preferred optimization method for the transfer alignment target function.

[0177] The Seagull Optimization Algorithm-based transfer alignment target function equivalent function optimization process includes seagull population initialization, migration movement and spiral attack prey.

[0178] In the seagull population initialization, the population needs to be distributed in the numerical range to be solved according to reasonable rules. For the unknown large installation error to be obtained by transfer alignment in the present application, the to-be-solved quantities include the heading angle installation error , the pitch angle installation error and the roll angle installation error , which constitute a three-dimensional search space.

[0179] The initialization of the three-dimensional position of the population is represented as:

[0180] ………………………(22)

[0181] In the formula:

[0182] the heading angle installation error corresponding population position vector;

[0183] the pitch angle installation error corresponding population position vector;

[0184] the roll angle installation error corresponding population position vector;

[0185] N-dimensional random number sequence vector, N represents the number of seagull population, the random number value range is greater than 0 and less than 1;

[0186] , Lower and upper bounds of the installation error value of the heading angle, wherein , ;

[0187] , Lower and upper bounds of the installation error value of the pitch angle, wherein , ;

[0188] , Lower and upper bounds of the installation error value of the roll angle, wherein , .

[0189] Calculate the fitness of the population at this time (i.e. pass the alignment target function value), and obtain the best individual:

[0190] ………………………(23)

[0191] In the formula:

[0192] Fitness of the nth population;

[0193] Maximum fitness;

[0194] Installation error matrix represented by the heading, pitch and roll installation error angles corresponding to the nth seagull individual;

[0195] Position of the seagull individual with the maximum fitness.

[0196] Subsequently, the migration movement and attack of the seagull population will be completed according to the above initialization results within a given number of algorithm iterations.

[0197] In the migration movement, the movement of the seagull population in the search space should avoid mutual collision and approach the best individual.

[0198] 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:

[0199] ……………………………(24)

[0200] In the formula:

[0201] - control parameters;

[0202] - motion behavior of the gulls in the search space;

[0203] - random number balancing global search and local search;

[0204] - migration moving direction of the gull population.

[0205] In the spiral attack on the prey, the gull population will perform three-dimensional spiral motion in the air to approach the prey target, and its behavior of attacking the prey can be understood as updating towards the global optimal solution of the transfer alignment target function.

[0206] The spiral motion of the gull population is represented as:

[0207] …………………………………(25)

[0208] In the formula:

[0209] - spiral motion radius;

[0210] 、 - shape control parameter of the spiral motion;

[0211] - attack angle random number, value range ;

[0212] 、 、 - coordinates of the spiral motion transformed into three-dimensional space.

[0213] Finally, the position update completed by the gull population is represented as:

[0214] ……………………………(26)

[0215] After completing the position update, the fitness of the updated population and the best individual are recalculated 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 estimate value , the pitch angle installation error estimate value , and the roll angle installation error estimate value .

[0216] In summary, the installation error matrix can be obtained based on the above installation error estimates, thus completing the transfer alignment of unknown large installation errors.

[0217] It should be noted that the Seagull optimization algorithm is used in this invention to optimize the constructed objective function in order to achieve the transfer alignment for unknown large installation errors. Transfer alignment methods that use other intelligent optimization algorithms to calculate the objective function constructed in this invention should also be within the protection scope of this invention.

[0218] To verify the effectiveness of this invention, numerical simulation experiments were conducted. Considering the underwater robot was fixed to the underwater main platform before release, the heading installation error angle between the underwater robot's micro-inertial navigation system and the high-precision inertial navigation system of the underwater main platform was set to 56°, the pitch installation error angle to 0.4°, and the roll installation error angle to -0.3°. The gyroscope zero-bias stability in the underwater robot's micro-inertial navigation system was 1° / h, and the accelerometer zero-bias stability was 0.2mg. The maneuvers performed by the underwater main platform included acceleration and turning. In the seagull optimization algorithm, the seagull population size was set to 1000, the maximum number of iterations was set to 100, and the shape control parameters for the helical motion were... and All are set to 1. The transfer alignment time is set to 60s. The heading installation error estimation result obtained using the transfer alignment method proposed in this invention is as follows: Figure 3 As shown, the pitch installation error estimation results are as follows: Figure 4 As shown, the roll installation error estimation results are as follows: Figure 5 As shown in the figure. Experimental results demonstrate that the method proposed in this invention can achieve the transmission and alignment of large-angle installation errors of the micro-inertial navigation system on underwater platforms.

[0219] like Figure 6 As shown, the computer device includes a processor, memory, and network interface connected via a system bus. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and may also store a computer program. When executed by the processor, this computer program enables the processor to implement a large-angle installation error transfer alignment method applied to micro-inertial navigation systems on underwater platforms. The internal memory may also store a computer program, which, when executed by the processor, enables the processor to implement the large-angle installation error transfer alignment method applied to micro-inertial navigation systems on underwater platforms. Those skilled in the art will understand that… Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0220] In one embodiment, a computer device is provided, comprising a memory and a processor, the memory storing a computer program, the computer program being executed by the processor to cause the processor to perform the following steps:

[0221] S1, receiving navigation information output by a main platform high-precision inertial navigation system, and calculating analog data of a main inertial gyro and analog data of a main inertial accelerometer of the high-precision inertial navigation system through an inversion algorithm, the navigation information comprising attitude, velocity and position information;

[0222] S2, receiving gyro measurement data and accelerometer measurement data output by a micro inertial navigation system, and combining the analog data of the main inertial gyro and the analog data of the main inertial accelerometer obtained in S1 to construct a transfer alignment target function with installation errors of the micro inertial navigation system relative to the high-precision inertial navigation system as variables;

[0223] S3, using an optimization algorithm to optimize the transfer alignment target function to obtain an estimated value of the installation errors to determine installation errors between the micro inertial navigation system and the high-precision inertial navigation system;

[0224] In S2, the transfer alignment target function is constructed as:

[0225]

[0226] In the formula:

[0227] is a gyro measurement value of a micro inertial navigation system of a sub-platform at i moment;

[0228] is an accelerometer measurement value of the micro inertial navigation system of the sub-platform at i moment;

[0229] is an analog value of a main inertial accelerometer at i moment;

[0230] is an analog value of a main inertial gyro at i moment;

[0231] is a real result of an installation error matrix, the installation error matrix being composed of installation errors between a main inertial navigation system and a micro inertial navigation system, represented by a heading angle installation error , a pitch angle installation error and a roll angle installation error ;

[0232] is an estimated result of the installation error matrix obtained by transfer alignment;

[0233] is a norm of a vector ;

[0234] k represents the k-th moment.

[0235] In one embodiment, a computer readable storage medium is provided, which stores a computer program, when the computer program is executed by a processor, the processor executes the following steps:

[0236] S1, receiving navigation information output by a high-precision inertial navigation system of a main platform, and calculating analog data of a main inertial gyro and analog data of a main inertial accelerometer of the high-precision inertial navigation system through an inversion algorithm, the navigation information including attitude, velocity and position information;

[0237] S2, receiving gyro measurement data and accelerometer measurement data output by a micro inertial navigation system, and combining the analog data of the main inertial gyro and the analog data of the main inertial accelerometer obtained in S1, to construct a transfer alignment target function with installation errors of the micro inertial navigation system relative to the high-precision inertial navigation system as variables;

[0238] S3, using an optimization algorithm to optimize the transfer alignment target function, to obtain an estimated value of the installation errors, so as to determine installation errors between the micro inertial navigation system and the high-precision inertial navigation system;

[0239] In S2, the transfer alignment target function is constructed as:

[0240]

[0241] In the formula:

[0242] is a gyro measurement value of a micro inertial navigation system of a sub-platform at i-th moment;

[0243] is an accelerometer measurement value of the micro inertial navigation system of the sub-platform at the i-th moment;

[0244] is an analog value of a main inertial accelerometer at the i-th moment;

[0245] is an analog value of a main inertial gyro at the i-th moment;

[0246] is a true result of an installation error matrix, the installation error matrix being composed of installation errors between a main inertial navigation system and a sub-inertial navigation system, the installation errors including a heading angle installation error , a pitch angle installation error and a roll angle installation error ;

[0247] is an estimated result of the installation error matrix obtained by transfer alignment;

[0248] is the norm of vector

[0249] k represents the k-th moment.

[0250] It is understood by those skilled in the art that all or part of the processes in the above-mentioned embodiment methods can be completed by a computer program instructing relevant hardware. The program can be stored in a non-volatile computer readable storage medium, and when executed, can include the processes of the above-mentioned embodiment methods. Any reference to memory, storage, database or other medium used in the embodiments 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.

[0251] 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 the technical solutions recorded in the foregoing embodiments can be modified, or some technical features can be replaced by equivalent ones; and these modifications or replacements do not make 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 underwater micro-inertial navigation large-angle installation error transfer alignment, characterized in that, The method comprises 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 analog data of a main inertial navigation accelerometer of the high-precision inertial navigation system through an inversion algorithm, wherein the navigation information comprises attitude, speed and position information; S2, receiving gyroscope measurement data and accelerometer measurement data output by a micro inertial navigation system, 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 taking installation errors of the micro inertial navigation system relative to the high-precision inertial navigation system as variables; S3, performing optimization on the transfer alignment target function through an optimization algorithm to obtain an estimated value of the installation errors, so as to determine the installation errors 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, k represents a time point. 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; Aim is the analog value of the master inertial navigation accelerometer at time i; Gyroscope simulation value of master inertial navigation at time i; To install the error matrix real results, the main inertial navigation and installation error between the installation error matrix composed of sub-inertial navigation, by the heading angle installation error , pitch angle installation error And roll angle installation error Indicated; to pass the installation error matrix estimate obtained from the alignment; is the norm of the vector ​ 2. The method for underwater micro inertial navigation large-angle installation error transfer alignment according to claim 1, wherein, an equivalent function of the transfer alignment target function is constructed based on the transfer alignment target function, and only the influence of diagonal elements of the installation error matrix on the equivalent function of the transfer alignment target function is considered. The equivalent function of the transfer alignment target function is in the form of: In the formula, k represents a time point.

3. The method for underwater micro inertial navigation large-angle installation error transfer alignment according to claim 2, wherein, the equivalent function of the transfer alignment target function is in the form of: In the formula, k represents a time point. To pass the installation error matrix estimate results obtained by alignment; constructing an information matrix using the micro inertial navigation gyroscope, accelerometer measurement results and the analog data of the main inertial navigation gyroscope and accelerometer; is the sum of the diagonal elements of the matrix is the sum of the diagonal elements of the matrix 4. The method for underwater micro inertial navigation large-angle installation error transfer alignment according to claim 1, wherein, At time k, the information matrix is expressed as: In S1, when the analog data of the main inertial navigation accelerometer is calculated through the inversion algorithm, the paddle error is compensated. Gyroscope simulation value of master inertial navigation at time i; is the gyro 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.

5. The method for underwater micro inertial navigation large-angle installation error transfer alignment according to claim 1, wherein, In S1, when the analog data of the main inertial navigation gyroscope is calculated through the inversion algorithm, the equivalent rotation vector error is compensated.

6. The method for underwater micro inertial navigation large-angle installation error transfer alignment according to claim 1, wherein, In S3, the optimization algorithm is an intelligent optimization algorithm; and the intelligent optimization algorithm is a seagull optimization algorithm.

7. The method for underwater micro inertial navigation large-angle installation error transfer alignment according to claim 6, wherein, the step of performing optimization through 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.

8. A computer readable storage medium storing a computer program, wherein the computer program is executed by a processor to make the processor execute 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 the computer program is executed by the processor to make the processor execute the steps of the method according to any one of claims 1 to 7. ​ ​ ​

Images