Photoelectric load transfer alignment and error dynamic compensation method, device and equipment

Abstract

The invention discloses a photoelectric load transfer alignment and error dynamic compensation method, device and equipment, and belongs to the technical field of transfer error compensation. According to the method, collaborative modeling and an integrated compensation mechanism are carried out on multiple error sources, and large mounting angle alignment is optimized in combination with a virtual sub inertial navigation reference method. A dynamic environment adaptive alignment control strategy is realized, filtering parameters are optimized in real time according to flight states (such as acceleration and angular velocity), and alignment stability under complex electromagnetic interference is ensured. The transfer alignment technology is utilized to align the airborne photoelectric load system, so that the transfer alignment precision can be remarkably improved, accurate navigation and positioning are realized, and the execution efficiency of various tasks is enhanced. And meanwhile, the dependence on maneuvering characteristics and high-precision hardware is reduced, the cost is reduced, and the cost performance and the market competitiveness are improved. In addition, the application scene of the unmanned aerial vehicle is expanded, so that the unmanned aerial vehicle can reliably work in various complex environments, and multi-task requirements are met.

Description

Technical Field

[0001] This invention relates to the field of transmission error compensation technology, and in particular to a method, apparatus and equipment for photoelectric load transmission alignment and dynamic error compensation. Background Technology

[0002] In many modern operational domains, airborne optoelectronic payload systems (such as UAV pods) play a crucial role in target identification, reconnaissance, and strike missions. However, the initial alignment stage before mission execution faces numerous challenges. For airborne optoelectronic payload systems, accurate initial alignment is the cornerstone for ensuring the precise execution of subsequent missions. Only when the inertial navigation system within the pod successfully establishes a precise navigation coordinate system can a reliable reference be provided for various operations. Therefore, in-depth research and the proposal of practical solutions have significant theoretical and applied value for improving the combat effectiveness of airborne optoelectronic payload systems.

[0003] In the existing technology, airborne pod transfer alignment methods can be divided into two categories according to their principles and characteristics: autonomous alignment methods based on their own sensors and data processing, and non-autonomous alignment methods that rely on external information or equipment assistance.

[0004] Autonomous alignment methods: These methods primarily rely on the sensors and internal data processing algorithms equipped on the airborne pod itself to achieve alignment. They include ground calibration methods and inertial navigation system-based alignment methods. Ground calibration methods involve using specialized instruments on the ground to repeatedly adjust and calibrate installation errors based on the pod's structure and sensor characteristics. Inertial navigation system-based alignment methods utilize data acquired from sensors such as accelerometers and gyroscopes within the inertial navigation system, and then use complex algorithms to determine the pod's attitude and position to achieve alignment.

[0005] Non-autonomous alignment methods: These methods require external information, targets, or equipment to assist in the alignment of the airborne pod. These include in-flight calibration and optical alignment methods. In-flight calibration requires selecting a cooperative target with known coordinates within the aircraft's field of view during flight and using various relevant data for fitting and calculation to achieve calibration. Optical alignment methods require external optical equipment such as laser emitters and mirrors, determining the pod's position and attitude based on optical measurement principles.

[0006] Existing airborne pod alignment technologies all have some drawbacks. Among autonomous alignment methods, ground calibration is cumbersome, time-consuming, and labor-intensive, requiring repeated adjustments with specialized instruments. Moreover, the significant difference between the ground and air environments makes it difficult for calibration results to accurately reflect actual flight conditions. Furthermore, it lacks real-time calibration capabilities, making it impossible to adjust parameters promptly if they change during flight. Alignment methods based on inertial navigation systems suffer from low precision inertial devices, leading to significant error accumulation over long operating times, severely reducing alignment accuracy. They are also susceptible to interference from various factors such as measurement random noise, sensor malfunctions, modeling errors, and external disturbances, resulting in low reliability. Among non-autonomous alignment methods, the airborne calibration method has extremely stringent requirements on the aircraft's flight status and cooperative targets within the field of view. It cannot be implemented under complex weather conditions or in areas without obvious landmarks. Furthermore, data processing is complex, the computational load is huge, and it is prone to error accumulation and solution convergence problems, affecting the final accuracy. The optical alignment method makes the system more complex. The additional optical equipment increases both weight and cost, is difficult to install and debug, and has particularly high accuracy requirements. Moreover, the optical equipment is greatly affected by environmental factors such as dust, water vapor, and strong light, and the measurement accuracy can easily drop sharply or even fail. Summary of the Invention

[0007] In view of the above problems, the present invention provides a method, apparatus and device for photoelectric load transfer alignment and dynamic error compensation to overcome the above problems or at least partially solve the above problems.

[0008] This invention provides the following solution:

[0009] A method for aligning and dynamically compensating for photoelectric load transfer errors includes:

[0010] Step S1. System Initialization:

[0011] Set up the geocentric inertial coordinate system, the Earth coordinate system, the geographic coordinate system, the navigation coordinate system, and the vehicle coordinate system, and define the transformation relationships between the coordinate systems; calibrate the initial attitude, velocity, and position parameters of the main inertial navigation system and the sub-inertial navigation system;

[0012] Step S2. Error Modeling and Compensation:

[0013] A second-order Markov model for flexural deformation error and a geometric model for lever arm effect error are established.

[0014] The deflection angle is estimated in real time using a Kalman filter, and the measurement data of the main inertial navigation system and the sub-inertial navigation system are corrected. The speed of the lever arm is compensated for the speed measurement of the sub-inertial navigation system to obtain the corrected speed.

[0015] Step S3. Attitude and velocity matching filtering:

[0016] Define the state vector; construct the state equation and measurement equation;

[0017] The Kalman gain is iteratively updated using the state equation and the measurement equation to compensate for dynamic errors in real time.

[0018] Preferably, step S2 further includes:

[0019] In the navigation coordinate system, a virtual sub-inertial navigation reference is used, and its initial attitude is adjusted by rotation matrix or quaternion to make the virtual reference approximate the attitude of the actual sub-inertial navigation system.

[0020] Preferably, step S2 further includes:

[0021] Data transmission latency is measured using timestamp technology, and the measured data is synchronized and corrected during data processing.

[0022] Preferably, the second-order Markov model is represented by the following equation:

[0023]

[0024] In the formula: Let ξ be the deflection angle, then ξ = [ξ] x ξ y ξ z ] T For the angular velocity of deflection, η = [η x η y η z ] T Let β be the variance, and β = [β x β y β z ] T For the relevant time τ i Regarding the relevant model parameters, the variance of the deflection angle is defined as follows: σ η , σ θ ,β and τ i The relationship is as follows:

[0025]

[0026] Preferably, the geometric model of the lever arm effect error is expressed by the following formula:

[0027] V l =V m -V s =ω×r

[0028] In the formula: V m Main inertial navigation velocity, V s Let r be the velocity of the inertial navigation system, r be the lever vector, and ω be the angular velocity of the carrier.

[0029] Preferably, the state vector is represented by the following formula:

[0030]

[0031] In the formula: The misalignment angle corresponding to the attitude matrix of the carrier system; δυ=[δυ E δυ N δυ U ] represents the velocity errors in the east, north, and sky directions; ε = [ε x ε y ε z ] represents the constant drift of the gyroscope; ▽ = [▽] x ▽ y ▽ z ] represents constant drift of the table; μ represents installation error; θ represents flexural deformation angle; ω represents flexural deformation angular rate.

[0032] Preferably, the state equation is expressed by the following formula:

[0033]

[0034] In the formula: State variables The derivative; Let δυ be the derivative of the state variable; The derivative of the state variable ε; The derivative of the state variable ▽ The derivative of the state variable μ The derivative of the state variable θ. The derivative of the state variable μ;

[0035]

[0036] Let h be the radius of curvature of the meridian and the radius of curvature of the lateral meridian, L be the latitude, and f be the radius of curvature of the lateral meridian. n For the ratio of the sub-inertial navigation system in the n-frame, This is the rotation matrix from the carrier system to the navigation system.

[0037] Preferably, the measurement equation is expressed by the following formula:

[0038]

[0039] In the formula: The measured value of the misalignment angle. For the rotation matrix from the carrier system to the navigation system, Let be the rotation matrix from the carrier system (ba) to the sensor system (bs).

[0040] A photoelectric load transfer alignment and error dynamic compensation device includes:

[0041] An initialization unit is used to perform step S1 described above;

[0042] An error processing unit is used to perform step S2 described above;

[0043] The filtering calculation unit is used to perform step S3 as described above.

[0044] A photoelectric load transfer alignment and error dynamic compensation device, the device comprising a processor and a memory:

[0045] The memory is used to store program code and transmit the program code to the processor;

[0046] The processor is used to execute the above-described photoelectric load transfer alignment and error dynamic compensation method according to the instructions in the program code.

[0047] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0048] This application provides a method, apparatus, and device for optoelectronic payload transfer alignment and dynamic error compensation. The method employs collaborative modeling and an integrated compensation mechanism for multiple error sources, and optimizes large installation angle alignment using a virtual sub-inertial navigation reference method. It implements a dynamic environment adaptive alignment control strategy, optimizing filtering parameters in real time based on flight conditions (such as acceleration and angular velocity) to ensure alignment stability under complex electromagnetic interference. Utilizing transfer alignment technology to align airborne optoelectronic payload systems significantly improves transfer alignment accuracy, achieves precise navigation and positioning, and enhances the performance of various missions. Simultaneously, it reduces reliance on maneuverability and high-precision hardware, lowers costs, and improves cost-effectiveness and market competitiveness. Furthermore, it expands the application scenarios of unmanned aerial vehicles (UAVs), enabling them to operate reliably in various complex environments and meet diverse mission requirements.

[0049] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the embodiments will be briefly described below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0051] Figure 1 This is a flowchart of a photoelectric load transfer alignment and error dynamic compensation method provided in an embodiment of the present invention;

[0052] Figure 2 This is a structural diagram of the simulation model provided in the embodiments of the present invention;

[0053] Figure 3 This is a flowchart of the transfer alignment algorithm provided in an embodiment of the present invention;

[0054] Figure 4 This is a schematic diagram of an optoelectronic load transfer alignment and error dynamic compensation device provided in an embodiment of the present invention;

[0055] Figure 5 This is a schematic diagram of an optoelectronic load transfer alignment and error dynamic compensation device provided in an embodiment of the present invention. Detailed Implementation

[0056] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention are within the scope of protection of the present invention.

[0057] See Figure 1 This invention provides a method for aligning and dynamically compensating for photoelectric load transfer errors, as exemplified by [example of the invention]. Figure 1 As shown, the method may include:

[0058] Step S1. System Initialization:

[0059] Set up the geocentric inertial coordinate system, the Earth coordinate system, the geographic coordinate system, the navigation coordinate system, and the vehicle coordinate system, and define the transformation relationships between the coordinate systems; calibrate the initial attitude, velocity, and position parameters of the main inertial navigation system and the sub-inertial navigation system;

[0060] Step S2. Error Modeling and Compensation:

[0061] A second-order Markov model for flexural deformation error and a geometric model for lever arm effect error are established.

[0062] The deflection angle is estimated in real time using a Kalman filter, and the measurement data of the main inertial navigation system and the sub-inertial navigation system are corrected. The speed of the lever arm is compensated for the speed measurement of the sub-inertial navigation system to obtain the corrected speed.

[0063] In a specific implementation, it may also include:

[0064] In the navigation coordinate system, a virtual sub-inertial navigation reference is used, and its initial attitude is adjusted by rotation matrix or quaternion to make the virtual reference approximate the attitude of the actual sub-inertial navigation system.

[0065] Furthermore, it may also include:

[0066] Data transmission latency is measured using timestamp technology, and the measured data is synchronized and corrected during data processing.

[0067] The second-order Markov model is represented by the following equation:

[0068]

[0069] In the formula: Let ξ be the deflection angle, then ξ = [ξ] x ξ y ξ z ] T For the angular velocity of deflection, η = [η x η y η z ] T Let β be the variance, and β = [β x β y β z ] T For the relevant time τ i Regarding the relevant model parameters, the variance of the deflection angle is defined as follows: σ η , β and τ i The relationship is as follows:

[0070]

[0071] The geometric model of the lever arm effect error is expressed by the following equation:

[0072]

[0073] In the formula: V m Main inertial navigation velocity, V s Let r be the velocity of the inertial navigation system, r be the lever vector, and ω be the angular velocity of the carrier.

[0074] Step S3. Attitude and velocity matching filtering:

[0075] Define a state vector; construct the state equation and measurement equation; the state vector is represented by the following equation:

[0076]

[0077] In the formula: The misalignment angle corresponding to the attitude matrix of the carrier system; δυ=[δυ E δυ N δυ U ] represents the velocity errors in the east, north, and sky directions; ε = [ε x ε y ε z ] represents the constant drift of the gyroscope; ▽ = [▽] x ▽ y ▽ z] represents constant drift of the table; μ represents installation error; θ represents flexural deformation angle; ω represents flexural deformation angular rate.

[0078] The state equation is expressed by the following equation:

[0079]

[0080] In the formula: State variables The derivative; The derivative of the state variable δv; The derivative of the state variable ε; The derivative of the state variable ▽ The derivative of the state variable μ The derivative of the state variable θ. The derivative of the state variable ω;

[0081] R N and R N These are the meridian radius of curvature and the gyroscopic radius of curvature, respectively; h is the local altitude; L is the latitude; f n For the ratio of the sub-inertial navigation system in the n-frame, This is the rotation matrix from the carrier system to the navigation system.

[0082] The measurement equation is expressed by the following formula:

[0083]

[0084] In the formula: The measured value of the misalignment angle. For the rotation matrix from the carrier system to the navigation system, Let be the rotation matrix from the carrier system (ba) to the sensor system (bs).

[0085] The Kalman gain is iteratively updated using the state equation and the measurement equation to compensate for dynamic errors in real time.

[0086] The optoelectronic load transfer alignment and error dynamic compensation method provided in this application accurately analyzes and models errors such as installation deviation angle, deflection angle, lever effect, and data transmission delay. In particular, the second-order Markov model for deflection and the measurement information compensation model for lever effect effectively improve the alignment accuracy of the airborne optoelectronic load system. A combined matching method of "velocity + attitude" (based on measurement misalignment angle matching) is proposed, and filtering algorithms are optimized for different misalignment angles, such as improved unscented Kalman filtering and adaptive Kalman filtering. The method combines virtual sub-inertial navigation reference method to handle large installation angle problems, enhancing alignment reliability. It achieves high-precision installation error angle estimation requiring only wing-mounted maneuver excitation and maintains good robustness in complex electromagnetic and dynamic flight environments, improving the system's applicability under various operating conditions.

[0087] The photoelectric load transfer alignment and error dynamic compensation method provided in this application will be described in detail below.

[0088] The optoelectronic payload transfer alignment and error dynamic compensation method provided in this application aims to overcome many shortcomings of existing airborne pod alignment technologies and achieve accurate, efficient, and reliable transfer alignment. On one hand, addressing the limitations of autonomous methods such as poor environmental adaptability, error accumulation, and complex operation, innovative algorithms and optimized processes are used to reduce the impact of inertial device accuracy and external interference, ensuring rapid and stable initial alignment under various operating conditions and improving mission response speed. On the other hand, given that non-autonomous methods are heavily constrained by external conditions—for example, airborne calibration methods rely on cooperative targets, and optical methods are susceptible to environmental interference—multi-source information fusion technology is employed, and backup and adaptive adjustment mechanisms are designed to ensure accurate pod alignment even in extreme conditions, enhancing the pod's overall combat effectiveness and meeting the requirements for high-precision and high-stability alignment.

[0089] In its specific implementation:

[0090] I. System Initialization.

[0091] (1) Coordinate System Definition and Transformation: During the UAV startup phase, the geocentric inertial coordinate system, Earth coordinate system, geographic coordinate system, navigation coordinate system, and carrier coordinate system are clearly defined. The transformation relationships between each coordinate system are defined in detail to provide a unified and accurate reference framework for subsequent navigation calculations and alignment processes. This process is based on the geographical characteristics of the Earth, such as its rotation and revolution, as well as the flight mission requirements of the UAV, to ensure the accuracy of coordinate system transformations and lay the foundation for precise navigation.

[0092] (2) Inertial Navigation System Parameter Calibration: The initial attitude, velocity, and position parameters of the main and sub-inertial navigation systems are calibrated. High-precision calibration equipment, such as ground reference stations and inertial measurement unit calibration platforms, is used to obtain accurate initial data. Through multiple measurements and data processing, initial errors are reduced to ensure the consistency and accuracy of the main and sub-inertial navigation systems in their initial state.

[0093] II. Error Modeling and Compensation.

[0094] (1) Modeling and compensation of flexural deformation error.

[0095] Modeling: Deformation data of the airframe structure is collected in real time using strain sensors, accelerometers, and other devices installed on key parts of the UAV. This data is analyzed using Fast Fourier Transform (FFT) to determine the frequency characteristics and autocorrelation of the flexural deformation. Based on the analysis results, the flexural deformation is modeled as an independent second-order Markov process. Taking a specific axis as an example, its second-order Markov model for flexural deformation is as follows:

[0096]

[0097]

[0098] Model parameters.

[0099] Define the variance of the deflection angle as σ η , β and τ i The relationship is as follows:

[0100]

[0101] Compensation: The deflection angle is introduced into the state variable, and a Kalman filter is used to estimate the deflection angle in real time. In the transfer alignment algorithm, the measurement data of the main and sub-inertial navigation systems are corrected based on the estimated deflection angle to eliminate the influence of deflection deformation on transfer alignment.

[0102] (2) Modeling and compensation of lever arm effect error.

[0103] Modeling: During the UAV design phase, the installation center deviation between the main and sub-inertial navigation systems is determined through precise measurement, and a geometric model of the lever effect is established, such as... Figure 1 As shown. During the alignment process, the influence of the lever arm effect on velocity measurement is analyzed. Assume the main inertial navigation velocity is V. m The inertial navigation velocity is V s If the lever arm vector is r and the angular velocity of the carrier is ω, then the velocity error caused by the lever arm effect is:

[0104] V l =V m -V s =ω×r

[0105] Compensation: A measurement information compensation method is used to compensate for the lever arm speed during the transfer alignment process. Specifically, the sub-inertial navigation speed measurement value is corrected, and the corrected speed is then used in subsequent transfer alignment calculations.

[0106] (3) Other error compensation.

[0107] To address the large installation angle problem, a virtual sub-INS reference method is introduced. A virtual reference for a sub-INS is created within the navigation coordinate system of the main INS. This virtual reference initially mirrors the main INS, but its attitude can be adjusted through mathematical transformations (such as rotation matrices or quaternions) to more closely approximate the initial attitude of the actual sub-INS. This virtual reference effectively simplifies the alignment process under large installation angle conditions and improves alignment accuracy. In the transfer alignment algorithm, the installation deviation angle is used as a state variable, and a Kalman filter is employed for real-time estimation and compensation. For data transmission delay errors, timestamp technology is used to accurately measure the data transmission delay. During data processing, the measured data is synchronized and corrected to eliminate the impact of delay errors.

[0108] III. Attitude + Velocity Matched Filtering Model.

[0109] Choose a 21-dimensional state vector Among them The misalignment angle corresponding to the attitude matrix of the carrier system; δυ=[δυ E δυ N δυ U ] represents the velocity errors in the east, north, and sky directions; ε = [ε x ε y ε z ] represents the constant drift of the gyroscope; ▽ = [▽] x ▽ y ▽ z [This refers to the drift of constant values ​​in the addition table;] (μ) represents the installation error; (abbreviated as θ) is the flexural deformation angle; (abbreviated as ω) is the angular velocity of flexural deformation.

[0110] Equations of state:

[0111]

[0112] in, State variables The derivative; The derivative of the state variable; The derivative of the state variable ε; The derivative of the state variable ▽; Let be the local angular rate of rotation of the n-frame relative to the i-frame.

[0113]

[0114] Among them, R Nand R N These are the meridian radius of curvature and the gyroscopic radius of curvature, respectively; h is the local altitude; L is the latitude; f n The specific force of the sub-inertial navigation system in the n-frame;

[0115] Measurement equation:

[0116]

[0117] The Kalman gain is updated iteratively using the state equation and measurement equation to compensate for dynamic errors in real time.

[0118] IV. Simulation Process:

[0119] The vehicle's maneuvering method and external interference all have varying degrees of impact on the performance of the transfer alignment. Therefore, simulation experiments are needed to test various matching methods under different maneuvering conditions and external environments. Figure 1 This is a structural diagram of the simulation model. Figure 2 This provides a flowchart of the alignment algorithm, thus offering a theoretical basis for its final practical application.

[0120] In summary, the optoelectronic payload transfer alignment and dynamic error compensation method provided in this application employs collaborative modeling and integrated compensation mechanisms for multiple error sources, and optimizes large installation angle alignment using a virtual sub-inertial navigation reference method. It implements a dynamic environment adaptive alignment control strategy, optimizing filtering parameters in real time based on flight conditions (such as acceleration and angular velocity) to ensure alignment stability under complex electromagnetic interference. Utilizing transfer alignment technology to align airborne optoelectronic payload systems significantly improves transfer alignment accuracy, achieves precise navigation and positioning, and enhances the performance of various missions. Simultaneously, it reduces reliance on maneuverability and high-precision hardware, lowers costs, and improves cost-effectiveness and market competitiveness. Furthermore, it expands the application scenarios of UAVs, enabling them to operate reliably in various complex environments and meet diverse mission requirements.

[0121] See Figure 4 This application embodiment can also provide a photoelectric load transfer alignment and error dynamic compensation device, such as... Figure 4 As shown, the device for performing the above-described photoelectric load transfer alignment and error dynamic compensation method may include:

[0122] Initialization unit 401 is used to perform the above step S1;

[0123] Error processing unit 402 is used to perform step S2 as described above;

[0124] The filter calculation unit 403 is used to perform the above step S3.

[0125] This application embodiment can also provide an optoelectronic load transfer alignment and error dynamic compensation device, the device including a processor and a memory:

[0126] The memory is used to store program code and transmit the program code to the processor;

[0127] The processor is used to execute the steps of the above-described photoelectric load transfer alignment and error dynamic compensation method according to the instructions in the program code.

[0128] like Figure 5 As shown in the figure, the optoelectronic load transfer alignment and error dynamic compensation device provided in this application embodiment may include: a processor 10, a memory 11, a communication interface 12, and a communication bus 13. The processor 10, memory 11, and communication interface 12 all communicate with each other through the communication bus 13.

[0129] In this embodiment, the processor 10 may be a central processing unit (CPU), a graphics processing unit (GPU), an application-specific integrated circuit, a digital signal processor, a field-programmable gate array, or other programmable logic devices.

[0130] The processor 10 can call the program stored in the memory 11. Specifically, the processor 10 can execute the operations in the embodiment of the photoelectric load transfer alignment and error dynamic compensation method.

[0131] The memory 11 is used to store one or more programs. The programs may include program code, which includes computer operation instructions. In this embodiment, the memory 11 stores at least a program for implementing the following functions:

[0132] S1. System Initialization:

[0133] Set up the geocentric inertial coordinate system, the Earth coordinate system, the geographic coordinate system, the navigation coordinate system, and the vehicle coordinate system, and define the transformation relationships between the coordinate systems; calibrate the initial attitude, velocity, and position parameters of the main inertial navigation system and the sub-inertial navigation system;

[0134] S2. Error Modeling and Compensation:

[0135] A second-order Markov model for flexural deformation error and a geometric model for lever arm effect error are established.

[0136] The deflection angle is estimated in real time using a Kalman filter, and the measurement data of the main inertial navigation system and the sub-inertial navigation system are corrected. The speed of the lever arm is compensated for the speed measurement of the sub-inertial navigation system to obtain the corrected speed.

[0137] S3. Attitude and velocity matching filtering:

[0138] Define the state vector; construct the state equation and measurement equation;

[0139] The Kalman gain is updated iteratively using the state equation and measurement equation to compensate for dynamic errors in real time.

[0140] In one possible implementation, the memory 11 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function (such as file creation or data read / write). The data storage area may store data created during use, such as initialization data.

[0141] In addition, memory 11 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device or other volatile solid-state storage device.

[0142] Communication interface 12 can be an interface for a communication model, used to connect with other devices or systems.

[0143] Of course, it should be noted that, Figure 5 The structure shown does not constitute a limitation on the optoelectronic load transfer alignment and error dynamic compensation device in the embodiments of this application. In practical applications, the optoelectronic load transfer alignment and error dynamic compensation device may include more than Figure 5 More or fewer components as shown, or combinations of certain components.

[0144] This application embodiment may also provide a computer-readable storage medium for storing program code for executing the steps of the above-described photoelectric load transfer alignment and error dynamic compensation method.

[0145] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0146] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[0147] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for system or system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and relevant parts can be referred to the descriptions in the method embodiments. The systems and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0148] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of protection of the present invention.

Claims

1. A method for photoelectric load transfer alignment and dynamic error compensation, characterized in that, include: Step S1. System Initialization: Establish the geocentric inertial coordinate system, the Earth coordinate system, the geographic coordinate system, the navigation coordinate system, and the vehicle coordinate system, and define the transformation relationships between the coordinate systems; Calibrate the initial attitude, velocity, and position parameters of the main inertial navigation system and the sub-inertial navigation system; Step S2. Error Modeling and Compensation: A second-order Markov model for flexural deformation error and a geometric model for lever arm effect error are established. The deflection angle is estimated in real time using a Kalman filter, and the measurement data of the main inertial navigation system and the sub-inertial navigation system are corrected. The speed of the lever arm is compensated for the speed measurement of the sub-inertial navigation system to obtain the corrected speed. Step S3. Attitude and velocity matching filtering: Define the state vector; construct the state equation and measurement equation; The Kalman gain is iteratively updated using the state equation and the measurement equation to compensate for dynamic errors in real time.

2. The photoelectric load transfer alignment and error dynamic compensation method according to claim 1, characterized in that, Step S2 further includes: In the navigation coordinate system, a virtual sub-inertial navigation reference is used, and its initial attitude is adjusted by rotation matrix or quaternion to make the virtual reference approximate the attitude of the actual sub-inertial navigation system.

3. The photoelectric load transfer alignment and error dynamic compensation method according to claim 1, characterized in that, Step S2 further includes: Data transmission latency is measured using timestamp technology, and the measured data is synchronized and corrected during data processing.

4. The photoelectric load transfer alignment and error dynamic compensation method according to claim 1, characterized in that, The second-order Markov model is represented by the following equation: In the formula: Let ξ be the deflection angle, then ξ = [ξ] x ξ y ξ z ] T For the angular velocity of deflection, η = [η x η y η z ] T Let β be the variance, and β = [β x β y β z ] T To be related to time τ i Regarding the relevant model parameters, the variance of the deflection angle is defined as follows: β and τ i The relationship is as follows:

5. The photoelectric load transfer alignment and error dynamic compensation method according to claim 1, characterized in that, The geometric model of the lever arm effect error is expressed by the following equation: V l =V m -V s =ω×r In the formula: V m Main inertial navigation velocity, V s Let r be the velocity of the inertial navigation system, r be the lever vector, and ω be the angular velocity of the carrier.

6. The photoelectric load transfer alignment and error dynamic compensation method according to claim 1, characterized in that, The state vector is represented by the following equation: In the formula: The misalignment angle corresponding to the attitude matrix of the carrier system; δυ=[δυ E δυ N δυ U ] represents the velocity errors in the east, north, and sky directions; ε = [ε x ε y ε z ] represents the constant drift of the gyroscope; ▽ = [▽] x ▽ y ▽ z ] represents constant drift of the table; μ represents installation error; θ represents flexural deformation angle; ω represents flexural deformation angular rate.

7. The photoelectric load transfer alignment and error dynamic compensation method according to claim 1, characterized in that, The state equation is expressed by the following equation: In the formula: State variables The derivative; The derivative of the state variable δυ; The derivative of the state variable ε; The derivative of the state variable ▽ The derivative of the state variable μ. The derivative of the state variable θ. The derivative of the state variable ω; R N and R N These are the meridian radius of curvature and the gyroscopic radius of curvature, respectively; h is the local altitude; L is the latitude; f n For the ratio of the sub-inertial navigation system in the n-frame, This is the rotation matrix from the carrier system to the navigation system.

8. The photoelectric load transfer alignment and error dynamic compensation method according to claim 1, characterized in that, The measurement equation is expressed by the following formula: In the formula: The measured value of the misalignment angle. For the rotation matrix from the carrier system to the navigation system, Let be the rotation matrix from the carrier system (ba) to the sensor system (bs).

9. A photoelectric load transfer alignment and error dynamic compensation device, characterized in that, include: An initialization unit is configured to perform step S1 as described in any one of claims 1 to 8; An error processing unit is configured to perform step S2 as described in any one of claims 1 to 8; A filtering calculation unit is used to perform step S3 as described in any one of claims 1 to 8.

10. A photoelectric load transfer alignment and error dynamic compensation device, characterized in that, The device includes a processor and a memory: The memory is used to store program code and transmit the program code to the processor; The processor is used to execute the photoelectric load transfer alignment and error dynamic compensation method according to any one of claims 1-8 according to the instructions in the program code.

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