Optical satellite multi-source data fusion attitude determination method without high-precision gyroscope

Abstract

The invention relates to an optical satellite multi-source data fusion attitude determination method without a high-precision gyroscope. The invention relates to the technical field of aerospace. Satellite attitude kinematics and dynamics modeling is carried out, and kinematics equation modeling of attitude estimation is carried out; performing kinetic equation modeling of attitude estimation; carrying out zero offset estimation error equation modeling; modeling an observation equation; and performing multi-source data fusion attitude determination according to a modeling result. According to the invention, organic fusion is carried out by combining attitude kinematics and kinetic equations of satellites, high-robustness, high-precision and high-reliability attitude determination is realized, the development cost of batch optical remote sensing satellites is greatly reduced, the attitude determination and control precision of the satellites is ensured, and high-quality image acquisition is realized. The designed method is simple in structure, high in economic value and suitable for the design of the attitude determination system of the batch low-cost optical remote sensing satellite in engineering practice.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of aerospace technology, and is a multi-source data fusion attitude determination method for optical satellites without high-precision gyroscopes. BACKGROUND

[0002] In recent years, space technology and microelectronic technology have developed rapidly, and the construction of optical remote sensing satellites has changed rapidly. Unlike traditional large-scale optical remote sensing satellites, such as WorldView and Spot satellites, which use high-cost, high-precision optical systems and high-precision attitude measurement and control components, the current design of optical remote sensing satellites is developing towards low cost, low mass and mass production. Through technical iteration, a number of large-scale optical remote sensing satellite constellations have been built in the world, such as the Jilin-1 constellation and the Pigeon constellation. These optical remote sensing satellite constellations can achieve tens of times of imaging coverage on the ground through a large number of satellites, and have the ability to quickly acquire remote sensing data in a wide area. The attitude determination accuracy of optical remote sensing satellites is closely related to the quality of remote sensing images. However, the low-cost and lightweight design limits the accuracy of the attitude sensor. How to achieve high-precision attitude determination under the condition of low-precision sensors is the key and difficulty of mass production of optical satellites. The present application designs a multi-source data fusion attitude determination method for optical satellites without high-precision gyroscopes, which realizes high-precision attitude determination by fusing the existing multi-source attitude and related measurement data on the satellite without relying on high-precision fiber gyroscopes. SUMMARY

[0003] The present application provides a multi-source data fusion attitude determination method for optical satellites without high-precision gyroscopes, which realizes high-precision attitude determination for low-cost satellites and provides a basis for high-precision attitude control and high-quality image acquisition.

[0004] The present application provides the following technical solutions: A multi-source data fusion attitude determination method for optical satellites without high-precision gyroscopes, the method comprising the following steps: Step 1: performing satellite attitude kinematics and dynamics modeling; Step 2: performing kinematics equation modeling for attitude estimation; Step 3: performing dynamics equation modeling for attitude estimation; Step 4: performing zero bias estimation error equation modeling; Step 5: performing observation equation modeling; Step 6: performing multi-source data fusion attitude determination according to the modeling results established in steps 1 to 5.

[0005] Preferably, the step 1 is specifically: The attitude of optical remote sensing satellites is represented by Euler angles, rotation matrices or quaternions, where quaternions achieve global non-singular attitude representation, and attitude quaternions represent the satellite's coordinate system. Relative to the inertial coordinate system The posture, in which represents the scalar part of the quaternion, represents the vector part of the quaternion, express The transpose of , and the constraints are satisfied , the inverse of the quaternion is expressed as ; Two quaternions and The multiplication operation relationship is: (1) in: Represents a vector The antisymmetric matrix of ; Represents quaternion multiplication; According to the above calculation relationship, the attitude kinematics and dynamics of the satellite are: (2) in: represents the satellite's moment of inertia matrix; Indicates attitude angular velocity; represents the control angular momentum of the reaction flywheel; represents the control torque of the reaction flywheel; Represents the spatial environment interference torque.

[0006] Preferably, the step 2 is specifically as follows: Define the true attitude quaternion , the estimated attitude quaternion , then the estimated error of the quaternion is Calculated by the following formula: (3) The differential equation for the quaternion estimation error is: (4) in: Represents the estimated error quaternion scalar and vector parts of ; Indicates attitude angular velocity The estimated value of the given true attitude angular velocity is expressed as , represents the estimated error angular velocity, and is ; represents the model error; Represents a unit quaternion.

[0007] Preferably, the step 3 is specifically: According to step 2, the estimation error angular velocity is According to the model operation relationship, the differential equation is: (5) (6) Wherein, formula 6 represents the expansion form of the inertia matrix ; represents the inverse of the inertia matrix ; represents the disturbance torque estimation error, given the real space disturbance torque , the estimated space disturbance torque , then the disturbance torque estimation error can be expressed as ; represents the calculation of intermediate variables, represents the model error, The specific form of (7) Wherein: and are the components of vectors and ; The estimation error of the space environmental disturbance torque The transformation is very slow, and its differential equation is: (8)

[0008] Preferably, the step 4 is specifically: Define the zero offset of the gyroscope as , and its estimated value is , then the estimation error of the gyroscope zero offset is: (9) Considering that the gyroscope zero offset is approximately constant, its differential equation is: (10)

[0009] Preferably, the step 5 is specifically: Given the measured quaternion of the star sensor , then the observation value of the quaternion estimation error is : (11) Given the measured angular velocity of the gyroscope , then the observation value of the angular velocity estimation error is : (12)

[0010] Preferably, the step 6 is specifically: The state variable of the attitude estimation is defined as Combined with the state equation of the steps 1 to 5 and the observation equation of the step 5, the linear Kalman filter is used to estimate the attitude information, so as to realize the attitude determination under the multi-source data fusion.

[0011] An optical satellite multi-source data fusion attitude determination system without high-precision gyroscopes, comprising: A modeling module, which respectively performs satellite attitude kinematics and dynamics modeling, performs kinematics equation modeling for attitude estimation, performs dynamics equation modeling for attitude estimation, performs bias estimation error equation modeling, and performs observation equation modeling; A fusion attitude determination module, which performs multi-source data fusion attitude determination based on the modeling results.

[0012] A computer readable storage medium, which stores a computer program, the program being executed by a processor to implement an optical satellite multi-source data fusion attitude determination method without high-precision gyroscopes.

[0013] A computer device, comprising a memory and a processor, the memory storing a computer program, and the processor implementing an optical satellite multi-source data fusion attitude determination method without high-precision gyroscopes when executing the computer program.

[0014] The present application has the following advantages: The optical satellite multi-source data fusion attitude determination method without high-precision gyroscopes can realize high robustness, high precision and high reliability of attitude determination on the basis of only being equipped with low-cost and low-precision angular velocity measurement sensors, by organically fusing the measurement information available on the star, including low-precision attitude quaternion and angular velocity measurement information, torque information of attitude control, combining the satellite attitude kinematics and dynamics equations, greatly reducing the development cost of batch optical remote sensing satellites, ensuring the attitude determination and control precision, and realizing high-quality image acquisition. The designed method has simple structure and high economic value, and is suitable for the design of attitude determination system of batch low-cost optical remote sensing satellites in engineering practice. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the specific embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the specific 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 on the basis of these drawings.

[0016] Figure 1 The algorithm execution flowchart of the present application is shown; Figure 2 The attitude quaternion and its estimation curve of the present application are shown; Figure 3 The attitude angular velocity and its estimation curve of the present application are shown; Figure 4 The attitude quaternion estimation error curve of the present application is shown; Figure 5 The attitude angular velocity estimation error curve of the present application is shown. DETAILED DESCRIPTION

[0017] The technical solutions of the present application will be described clearly and completely below in combination with the drawings. Obviously, the described embodiments are some 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 fall within the protection scope of the present application.

[0018] The present application will be described in detail below in combination with specific embodiments. Embodiment one According to Figures 1 to 5 As shown in the figure, the specific optimization technical solution adopted by the present application to solve the above technical problems is: the present application relates to a high-precision gyro-free optical satellite multi-source data fusion attitude determination method.

[0020] The present application provides a high-precision gyro-free optical satellite multi-source data fusion attitude determination method, which comprises the following steps: Step 1: satellite attitude kinematics and dynamics modeling; Step 2: kinematics equation modeling for attitude estimation; Step 3: dynamics equation modeling for attitude estimation; Step 4: zero offset estimation error equation modeling; Step 5: observation equation modeling; Step 6: multi-source data fusion attitude determination according to the modeling results established in steps 1 to 5.

[0021] The optical satellite multi-source data fusion attitude determination method without high-precision gyroscopes designed by the application can realize high robustness, high precision and high reliability of attitude determination on the basis of only being equipped with low-cost and low-precision angular velocity measurement sensors, by organically fusing the measurement information available on the satellite, including low-precision attitude quaternion and angular velocity measurement information, torque information of attitude control, combining the satellite attitude kinematics and dynamics equation, greatly reducing the development cost of batch optical remote sensing satellites, ensuring the attitude determination and control precision, and realizing high-quality image acquisition. The designed method has simple structure and high economic value, and is suitable for the design of attitude determination system of batch low-cost optical remote sensing satellites in engineering practice. Specific embodiment two: The difference between the embodiment two and the embodiment one of the application is only that: The step 1 is specifically: The attitude of the optical remote sensing satellite is represented by Euler angles, rotation matrix or quaternion, wherein the quaternion realizes global non-singular attitude representation, and the attitude quaternion represents the attitude of the satellite body coordinate system relative to the inertial coordinate system , wherein represents the scalar part of the quaternion, represents the vector part of the quaternion, represents the transpose of , and satisfies the constraint condition , the inverse of the quaternion is ; the operation relationship of the multiplication of two quaternions is: (1) wherein: represents the skew-symmetric matrix of the vector ; and represents quaternion multiplication. According to the above operation relationship, the attitude kinematics and dynamics of the satellite are: (2) wherein: represents the rotation inertia matrix of the satellite; represents the attitude angular velocity; represents the control angular momentum of the reaction flywheel; represents the control torque of the reaction flywheel; represents the spatial environmental disturbance torque. Specific embodiment three: The difference between the embodiment three and the embodiment two of the application is only that: The step 2 is specifically: Define the true attitude quaternion , the estimated attitude quaternion , then the estimated error of the quaternion is Calculated by the following formula: (3) The differential equation for the quaternion estimation error is: (4) in: Represents the estimated error quaternion scalar and vector parts of ; Indicates attitude angular velocity The estimated value of the given true attitude angular velocity is expressed as , represents the estimated error angular velocity, and is ; represents the model error; Represents a unit quaternion. Specific embodiment four: The only difference between the fourth embodiment of the present application and the third embodiment is that: The step 3 is specifically as follows: According to step 2, the estimated error angular velocity is , then according to the model operation relationship, the differential equation is: (5) (6) Among them, Formula 6 represents the inertia matrix The expanded form of Represents the inertia matrix The inverse of Denotes the estimation error of the disturbance torque, given the real space disturbance torque , estimate the spatial interference moment , then the disturbance torque estimation error can be expressed as ; Indicates the calculation of intermediate variables, represents the model error, The specific form is: (7) in: and are vectors and The weight; Estimation error of space environment disturbance torque The transformation is very slow, and its differential equation is: (8) Embodiment five The difference between embodiment five and embodiment four is only that The step 4 is specifically The zero bias of the gyroscope is defined as The estimated value is The estimation error of the zero bias of the gyroscope is The estimation error of the zero bias of the gyroscope is (9) Considering that the zero bias of the gyroscope is approximately constant, the differential equation is (10) Embodiment six The difference between embodiment six and embodiment five is only that The step 5 is specifically The measured quaternion of the star sensor is given as The observation value of the estimation error of the quaternion is The observation value of the estimation error of the quaternion is (11) The measured angular velocity of the gyroscope is given as The observation value of the estimation error of the angular velocity is The observation value of the estimation error of the angular velocity is (12) Embodiment seven The difference between embodiment seven and embodiment six is only that The step 6 is specifically The state variable of the attitude estimation is defined as Combined with the state equations of the steps 1 to 5 and the observation equation of the step 5, a linear Kalman filter is used to estimate the attitude information, so as to realize the attitude determination under the multi-source data fusion. Embodiment eight The difference between embodiment eight and embodiment seven is only that The application provides an optical satellite multi-source data fusion attitude determination system without high-precision gyroscopes, which comprises: A modeling module, which respectively performs satellite attitude kinematics and dynamics modeling, performs kinematics equation modeling for attitude estimation, performs dynamics equation modeling for attitude estimation, performs zero bias estimation error equation modeling, and performs observation equation modeling; A fusion attitude determination module, which performs multi-source data fusion attitude determination based on the modeling results. Embodiment nine The difference between embodiment nine and embodiment eight is only that The application provides a computer readable storage medium, which stores a computer program, and the program is executed by a processor to implement an optical satellite multi-source data fusion attitude determination method without high-precision gyroscopes.

[0030] The method comprises the following steps: Step 1, satellite attitude kinematics and dynamics modeling: The attitude of an optical remote sensing satellite can be represented by Euler angles, a rotation matrix or a quaternion, wherein the quaternion can realize a globally non-singular attitude representation, and is therefore widely applied to satellite attitude determination and control system design. represents the attitude of a satellite body coordinate system relative to an inertial coordinate system , wherein represents the scalar part of the quaternion, represents the vector part of the quaternion, represents the transpose of , and satisfies the constraint condition . The inverse of the quaternion is represented as . The operation relationship of the multiplication of two quaternions and is as follows: (1) wherein: represents the skew-symmetric matrix of the vector ; and represents quaternion multiplication. According to the above operation relationship, the attitude kinematics and dynamics of the satellite are as follows: (2) wherein: represents the rotation inertia matrix of the satellite; represents the attitude angular velocity; represents the control angular momentum of the reaction flywheel; represents the control torque of the reaction flywheel; represents the space environmental disturbance torque.

[0031] Step 2, modeling of the kinematics equation of attitude estimation: Define the real attitude quaternion , the estimated attitude quaternion , and the estimation error of the quaternion can be calculated by the following formula: (3) The differential equation of the quaternion estimation error is as follows: (4) in: Represents the estimated error quaternion scalar and vector parts of ; Indicates attitude angular velocity The estimated value of the given true attitude angular velocity is expressed as , represents the estimated error angular velocity, and is ; represents the model error; Represents a unit quaternion.

[0032] Step 3: Modeling the dynamic equations for attitude estimation: According to step 2, the estimated error angular velocity is , then according to the model operation relationship, the differential equation can be obtained as follows: (5) in: (6) Represents the inertia matrix The expanded form of Represents the inertia matrix The inverse of Denotes the estimation error of the disturbance torque, given the real space disturbance torque , estimate the spatial interference moment , then the disturbance torque estimation error can be expressed as ; Indicates the calculation of intermediate variables, represents the model error, The specific form is: (7) in: and are vectors and The weight.

[0033] In addition, the estimation error of the space environment interference torque The transformation is very slow, so its differential equation is: (8) Step 4: Modeling the zero-bias estimation error equation: The gyro bias is defined as , whose estimated value is , then the estimated error of the gyro bias is for: (9) Considering that the gyro bias is approximately constant, its differential equation is: (10) Step 5, observation equation modeling: Given the measured quaternion of star sensor as , the observation value of the quaternion estimation error is : (11) Given the measured angular velocity of gyroscope as , the observation value of the angular velocity estimation error is : (12) Step 6, multi-source data fusion attitude determination: The state variable of attitude estimation is defined as , combined with the state equation of steps 1 to 5, and the observation equation of step 5, the linear Kalman filter is used to estimate the attitude information, so as to realize the attitude determination under multi-source data fusion. Specific embodiment ten: The difference between the embodiment ten and the embodiment nine is only that: The application provides a computer device, which comprises a memory and a processor, the memory stores a computer program, and the processor realizes a multi-source data fusion attitude determination method of an optical satellite without high-precision gyroscope when executing the computer program.

[0035] The method comprises the following steps: Step 1, satellite attitude kinematics and dynamics modeling: The attitude of an optical remote sensing satellite can be represented by Euler angles, rotation matrix or quaternion, wherein the quaternion can realize global non-singular attitude representation, and is widely used in satellite attitude determination and control system design. The attitude quaternion represents the attitude of the satellite body coordinate system relative to the inertial coordinate system , wherein represents the scalar part of the quaternion, represents the vector part of the quaternion, represents the transpose, and satisfies the constraint condition . The inverse of the quaternion is . The operation relationship of the multiplication of two quaternions and is: (1) wherein: represents the skew-symmetric matrix of the vector ; represents the quaternion multiplication. According to the above calculation relationship, the attitude kinematics and dynamics of the satellite are: (2) in: represents the satellite's moment of inertia matrix; Indicates attitude angular velocity; represents the control angular momentum of the reaction flywheel; represents the control torque of the reaction flywheel; Represents the spatial environment interference torque.

[0036] Step 2: Modeling the kinematic equations for posture estimation: Define the true attitude quaternion , the estimated attitude quaternion , then the estimated error of the quaternion is It can be calculated by the following formula: (3) The differential equation for the quaternion estimation error is: (4) in: Represents the estimated error quaternion scalar and vector parts of ; Indicates attitude angular velocity The estimated value of the given true attitude angular velocity is expressed as , represents the estimated error angular velocity, and is ; represents the model error; Represents a unit quaternion.

[0037] Step 3: Modeling the dynamic equations for attitude estimation: According to step 2, the estimated error angular velocity is , then according to the model operation relationship, the differential equation can be obtained as follows: (5) in: (6) Represents the inertia matrix The expanded form of Represents the inertia matrix The inverse of Denotes the estimation error of the disturbance torque, given the real space disturbance torque , estimate the spatial interference moment , then the disturbance torque estimation error can be expressed as ; denotes a calculation intermediate variable, denotes a model error, The specific form is: (7) Wherein: and are the components of the vector and .

[0038] In addition, the estimation error of the space environment disturbance torque The differential equation of the transformation is very slow: (8) Step 4, zero bias estimation error equation modeling: The zero bias of the gyroscope is defined as The estimated value is The estimation error of the gyroscope zero bias Is: (9) Considering that the gyroscope zero bias is approximately constant, the differential equation is: (10) Step 5, modeling the observation equation: Given the measured quaternion of the star sensor The observation value of the quaternion estimation error is : (11) Given the measured angular velocity of the gyroscope The observation value of the angular velocity estimation error is : (12) Step 6, multi-source data fusion attitude determination: The state variable of the attitude estimation is defined as Combined with the state equation of steps 1 to steps, and the observation equation of step 5, the linear Kalman filter is used to estimate the attitude information, which can realize the attitude determination under multi-source data fusion. Eleventh embodiment: The difference between the eleventh embodiment of the present application and the tenth embodiment is only: The purpose of the present application is to provide an optical satellite multi-source data fusion attitude determination method without high-precision gyroscope, to realize high-precision attitude determination of low-cost satellite, and to provide a basis for high-precision attitude control and high-quality image acquisition.

[0040] The patent of the application is realized by the following technical scheme. The optical satellite multi-source data fusion attitude determination method without high-precision gyro comprises the following steps: Step 1, satellite attitude kinematics and dynamics modeling: The attitude of an optical remote sensing satellite can be represented by Euler angles, rotation matrix or quaternion, wherein the quaternion can realize global non-singular attitude representation, and is widely applied to satellite attitude determination and control system design. The attitude of a satellite body coordinate system relative to an inertial coordinate system is represented by a quaternion, wherein represents the scalar part of the quaternion, represents the vector part of the quaternion, represents the transpose of , and satisfies the constraint condition . The inverse of the quaternion is represented as . The operation relationship of the multiplication of two quaternions and is as follows: (1) wherein: represents the skew-symmetric matrix of the vector ; and represents quaternion multiplication. According to the above operation relationship, the satellite attitude kinematics and dynamics are as follows: (2) wherein: represents the rotation inertia matrix of the satellite; represents the attitude angular velocity; represents the control angular momentum of the reaction flywheel; represents the control torque of the reaction flywheel; represents the space environment disturbance torque.

[0041] Step 2, modeling of the kinematics equation of attitude estimation: Define the real attitude quaternion , the estimated attitude quaternion , and the estimation error of the quaternion can be calculated by the following formula: (3) The differential equation of the quaternion estimation error is as follows: (4) wherein: represents the scalar and vector parts of the estimation error quaternion . denotes the estimated value of the attitude angular velocity; the given true attitude angular velocity is denoted as , denotes the estimated error angular velocity, and is ; denotes the model error; denotes the unit quaternion.

[0042] Step 3, modeling of the dynamics equation of attitude estimation: According to step 2, the estimated error angular velocity is , then according to the model operation relationship, the differential equation thereof can be obtained as: (5) wherein: (6) denotes the expansion form of the inertia matrix ; denotes the inverse of the inertia matrix ; denotes the disturbance torque estimation error, the given true space disturbance torque is denoted as , and the estimated space disturbance torque is denoted as , then the disturbance torque estimation error can be denoted as ; denotes a calculation intermediate variable, denotes the model error, and the specific form thereof is: (7) wherein: and are components of vectors and , respectively.

[0043] In addition, the estimation error of the space environmental disturbance torque is very slow to change, and thus the differential equation thereof is: (8) Step 4, modeling of the zero bias estimation error equation: The zero bias of the gyroscope is defined as , and the estimated value thereof is denoted as , then the estimation error of the gyroscope zero bias is: (9) Considering that the gyroscope zero bias is approximately constant, the differential equation thereof is: (10) Step 5, modeling of the observation equation: ​Given the measured quaternion of star sensor as , the observation of the quaternion estimation error is : (11) Given the measured angular velocity of gyro as , the observation of the angular velocity estimation error is : (12) Step 6, multi-source data fusion attitude determination: The state variable of attitude estimation is defined as , combined with the state equation of steps 1 to 5, and the observation equation of step 5, the linear Kalman filter is used to estimate the attitude information, which can realize the attitude determination under multi-source data fusion. Specific implementation method twelve: The patent is described in detail below with reference to the accompanying drawings. The patent provides an optical satellite multi-source data fusion attitude determination method without high-precision gyro, and the algorithm execution process is as shown in Figure 1 . The multi-source data fusion attitude determination method first predicts the attitude of the satellite and its related information through the attitude kinematics and dynamics equation of the satellite combined with the torque measurement information of the reaction flywheel. Then, according to the measured quaternion and angular velocity of star sensor and gyro, the predicted attitude information is corrected. This method uses the idea of multi-source data fusion to fuse the existing direct and indirect attitude measurement information on the satellite, and although high-precision gyro measurement angular velocity information is not used, excellent attitude determination accuracy can still be achieved.

[0045] The control method of the patent illustrates the attitude determination accuracy of the proposed method through an attitude control process of imaging on the ground. The analysis process is a total of 1000s, of which 0-500s is the three-axis attitude to the sun, after 500s, it is converted to three-axis stabilization to the ground, and 700s-1000s is the imaging process. The curves of attitude quaternion and its estimation are as shown in Figure 2 , and the curves of attitude angular velocity and its estimation are as shown in Figure 3 . From the figure, it can be observed that the estimated attitude information is completely coincided with the true attitude, and the attitude estimation dynamic characteristics are excellent. The attitude quaternion estimation error and angular velocity estimation error are as shown in Figures 4-5 . During the imaging period, the estimation error of quaternion is less than 2x10 -6 , corresponding to an attitude error of about 1.0", and the angular velocity estimation error is less than 5x10 -4 ° / s, the attitude estimation is accurate, which is much higher than the precision of the attitude sensor itself.

[0046] The related parameters of the embodiment are shown in Table 1 as follows: Table 1, related parameter table of embodiment

[0047] The above is only one preferred embodiment of the optical satellite multi-source data fusion attitude determination method without high-precision gyroscopes, and the protection scope of the optical satellite multi-source data fusion attitude determination method without high-precision gyroscopes is not limited to the above-mentioned embodiments. Any technical solution belonging to the idea shall belong to the protection scope of the present application. It should be pointed out that, for those skilled in the art, some improvements and changes without departing from the principles of the present application shall be considered as the protection scope of the present application.

Claims

1. A method for optical satellite multi-source data fusion attitude determination without a high-precision gyroscope, characterized by: The method comprises the following steps: Step 1: Conduct satellite attitude kinematics and dynamics modeling; Step 2: Model the kinematic equations for posture estimation; Step 3: Model the dynamic equations for posture estimation; Step 4: Model the zero-bias estimation error equation; Step 5: Observation equation modeling; Step 6: Based on the modeling results established in steps 1 to 5, perform multi-source data fusion and pose determination.

2. The method according to claim 1, wherein: The step 1 is specifically as follows: The attitude of optical remote sensing satellites is represented by Euler angles, rotation matrices or quaternions, where quaternions realize global non-singular attitude representation. Represents the satellite body coordinate system Relative to the inertial coordinate system The posture, in which represents the scalar part of the quaternion, represents the vector part of the quaternion, express The transpose of , and satisfy the constraints , the inverse of the quaternion is expressed as ; Two quaternions and The multiplication operation relationship is: (1) in: Represents a vector The antisymmetric matrix of ; Represents quaternion multiplication; According to the above calculation relationship, the attitude kinematics and dynamics of the satellite are: (2) in: represents the satellite's moment of inertia matrix; Indicates attitude angular velocity; represents the control angular momentum of the reaction flywheel; represents the control torque of the reaction flywheel; Represents the spatial environment interference torque.

3. The method according to claim 2, wherein: The step 2 is specifically as follows: Define the true attitude quaternion , the estimated attitude quaternion , then the estimated error of the quaternion is Calculated by the following formula: (3) The differential equation for quaternion estimation error is: (4) in: Represents the estimated error quaternion scalar and vector parts of ; Indicates attitude angular velocity The estimated value of the given true attitude angular velocity is expressed as , represents the estimated error angular velocity, and is ; represents the model error; Represents a unit quaternion.

4. The method according to claim 3, wherein: The step 3 is specifically as follows: According to step 2, the estimated error angular velocity is , then according to the model operation relationship, the differential equation is: (5) (6) Among them, Formula 6 represents the inertia matrix The expanded form of Represents the inertia matrix The inverse of Denotes the estimation error of the disturbance torque, given the real space disturbance torque , estimate the spatial interference moment , then the disturbance torque estimation error can be expressed as ; Indicates the calculation of intermediate variables, represents the model error, The specific form is: (7) in: and are vectors and The weight; Estimation error of space environment disturbance torque The transformation is very slow, and its differential equation is: (8)。 5. The method according to claim 4, wherein: The step 4 is specifically as follows: The gyro bias is defined as , whose estimated value is , then the estimated error of the gyro bias is for: (9) Considering that the gyro bias is approximately constant, its differential equation is: (10)。 6. The method according to claim 5, wherein: The step 5 is specifically as follows: The measurement quaternion of a given star sensor is , then the observed value of the quaternion estimation error is for: (11) The measured angular velocity of the given gyroscope is , then the observed value of the angular velocity estimation error is : (12)。 7. The method according to claim 6, wherein: The step 6 is specifically as follows: The state variables of pose estimation are defined as ,Combining the state equations from step 1 to step ,and the observation equation of step 5, a linear Kalman filter is used to estimate the ,attitude information to achieve attitude determination under multi-source data fusion.

8. An optical satellite multi-source data fusion attitude determination system without a high-precision gyroscope, characterized by: The system comprises: Modeling module, wherein the modeling module performs satellite attitude kinematics and dynamics modeling, performs kinematic equation modeling for attitude estimation, performs dynamic equation modeling for attitude estimation, performs zero bias estimation error equation modeling, and performs observation equation modeling; The fusion pose determination module performs multi-source data fusion pose determination based on the modeling results.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the method according to claims 1 to 7.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the method of claims 1-7 is implemented.

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