Unknown Interference and Attitude Estimation Method, Device and Medium during Satellite Maneuvering

Abstract

An embodiment of the present invention discloses a method, device and medium for estimating unknown interference and attitude during a satellite maneuver. The method may include: constructing an attitude control system model of the satellite based on the angular velocity and Euler angle of the satellite in a body coordinate system; designing a nonlinear interference observer for the attitude control system model using the constructed angular velocity channel model containing interference terms; discretizing the attitude control system model and obtaining a locally linearized attitude control system model based on Taylor expansion remainders; designing a maneuver controller for the satellite based on a proportional differential controller; designing a state / bias estimator to obtain an unbiased state estimation result and a bias estimation result, and obtaining an optimal state estimation value used as an attitude estimation result based on a coupling relationship between the bias estimation value and the state estimation value; and using the interference term observation value obtained by the nonlinear interference observer as an unknown interference estimation result.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of spacecraft attitude control, and in particular to a method, device, and medium for estimating unknown interference and attitude during satellite maneuvers. Background Art

[0002] Currently, in the development and application of new satellites, higher and higher requirements are placed on the satellite's maneuverability, and correspondingly, higher requirements are placed on the estimation accuracy of interference and attitude during satellite maneuvers.

[0003] At present, indirect methods are usually used to obtain interference and attitude estimation results during satellite maneuvers. For example, the interference estimation result is calculated during the attitude stabilization phase within a period of time before the attitude maneuver and is used as the interference value during the attitude maneuver; and certain variables obtained in the process of calculating the attitude estimation result during the attitude stabilization phase are used as certain variable values during the attitude maneuver; that is, the current conventional scheme is to reasonably utilize the interference estimation results and certain variables calculated during the attitude stabilization phase, and assume that they remain constant during the attitude maneuver, and then combine them with appropriate linear interference and attitude estimation algorithms to obtain the interference and attitude estimation results during the satellite maneuver, thereby avoiding singular values caused by directly estimating the interference and attitude during the maneuver.

[0004] However, in actual satellite attitude maneuvers, the attitude dynamics and kinematics mathematical models are difficult to linearize and simplify. In other words, to achieve higher precision and more agile maneuver control, a nonlinear system model must be established to more accurately describe the controlled object. Therefore, due to the complexity of nonlinear system models, nonlinear interference and attitude estimation schemes that can be applied to spacecraft attitude control are needed. Summary of the Invention

[0005] In view of this, the embodiments of the present invention hope to provide a method, device and medium for estimating unknown interference and attitude during satellite maneuvers; to achieve direct estimation of interference and attitude during satellite maneuvers, which has better real-time performance and is more conducive to on-orbit application compared to the indirect estimation scheme of conventional schemes.

[0006] The technical solution of the embodiment of the present invention is achieved as follows:

[0007] In a first aspect, an embodiment of the present invention provides a method for estimating unknown interference and attitude during satellite maneuvers, the method comprising:

[0008] Constructing an attitude control system model of the satellite based on the angular velocity and Euler angle of the satellite in the body coordinate system;

[0009] Designing a nonlinear disturbance observer for the attitude control system model using the constructed angular velocity channel model including disturbance terms;

[0010] Discretizing the attitude control system model and obtaining a locally linearized attitude control system model based on Taylor expansion remainders;

[0011] Designing a maneuver controller for the satellite based on a proportional-derivative controller;

[0012] A state / bias estimator is designed to obtain an unbiased state estimation result and a bias estimation result, and an optimal state estimation value used as a posture estimation result is obtained based on a coupling relationship between the bias estimation value and the state estimation value; and the interference term observation value obtained by the nonlinear interference observer is used as an unknown interference estimation result.

[0013] In a second aspect, an embodiment of the present invention provides a device for estimating unknown interference and attitude during satellite maneuvers, the device comprising: a system model building part, an observer design part, a discretization part, a controller design part, and an estimation part; wherein,

[0014] The system model building part is configured to build an attitude control system model of the satellite based on the angular velocity and Euler angle of the satellite in the body coordinate system;

[0015] The observer design part is configured to design a nonlinear disturbance observer for the attitude control system model using the constructed angular velocity channel model including the disturbance term;

[0016] The discretization part is configured to discretize the attitude control system model and obtain a locally linearized attitude control system model according to Taylor expansion remainders;

[0017] The controller design part is configured to design a maneuver controller of the satellite based on a proportional-derivative controller;

[0018] The estimation part is configured to obtain an unbiased state estimation result and a bias estimation result under the estimation of the state / bias estimator, and obtain an optimal state estimation value used as a posture estimation result based on the coupling relationship between the bias estimation value and the state estimation value; and use the interference term observation value obtained by the nonlinear interference observer as the unknown interference estimation result.

[0019] In a third aspect, an embodiment of the present invention provides a computing device, comprising: a communication interface, a memory, and a processor; each component is coupled together via a bus system, wherein:

[0020] The communication interface is used to receive and send signals when sending and receiving information with other external network elements;

[0021] The memory is used to store a computer program that can be run on the processor;

[0022] The processor is used to execute the steps of the unknown interference and attitude estimation method during satellite maneuvering described in the first aspect when running the computer program.

[0023] In a fourth aspect, an embodiment of the present invention provides a computer storage medium, which stores a program for estimating unknown interference and attitude during satellite maneuvers. When the program for estimating unknown interference and attitude during satellite maneuvers is executed by at least one processor, the steps of the method for estimating unknown interference and attitude during satellite maneuvers described in the first aspect are implemented.

[0024] Embodiments of the present invention provide a method, device, and medium for estimating unknown disturbances and attitude during satellite maneuvers. The method uses disturbance term observations obtained via a nonlinear disturbance observer as the unknown disturbance estimation result, discretizes the attitude control system model, and then performs local linearization. Finally, the system state is optimally estimated through the coupling relationship between the deviation estimate and the state estimate. This method achieves direct estimation of disturbances and attitude, offering better real-time performance than conventional indirect estimation schemes and is more suitable for on-orbit applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A schematic flow chart of a method for estimating unknown interference and attitude during satellite maneuvers provided by an embodiment of the present invention;

[0026] Figure 2 A schematic diagram of simulation of unknown interference observation results provided by an embodiment of the present invention;

[0027] Figure 3 A schematic diagram of the optimal estimation result of the attitude angular velocity provided by an embodiment of the present invention;

[0028] Figure 4 A schematic diagram of the optimal estimation result of Euler angles provided by an embodiment of the present invention;

[0029] Figure 5 A schematic diagram of the respective errors between the observed value and the estimated value of the attitude angular velocity provided by an embodiment of the present invention;

[0030] Figure 6 A schematic diagram of the respective errors between the observed and estimated values of the attitude angle provided in an embodiment of the present invention;

[0031] Figure 7 A schematic diagram of the error between the observed value and the state value of the unknown interference provided by an embodiment of the present invention;

[0032] Figure 8 A schematic diagram of a device for estimating unknown interference and attitude during satellite maneuvers provided by an embodiment of the present invention;

[0033] Figure 9 A schematic diagram of the specific hardware structure of a computing device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0034] The technical solutions in the embodiments of the present invention will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present invention.

[0035] To achieve direct estimation of interference and attitude during satellite maneuvers and improve accuracy, see Figure 1 , which shows a method for estimating unknown interference and attitude during satellite maneuvers provided by an embodiment of the present invention. The method may include:

[0036] S101: Constructing an attitude control system model of the satellite based on the angular velocity and Euler angle of the satellite in the body coordinate system;

[0037] S102: Designing a nonlinear disturbance observer for the attitude control system model using the constructed angular velocity channel model including the disturbance term;

[0038] S103: discretizing the attitude control system model and obtaining a locally linearized attitude control system model according to Taylor expansion remainders;

[0039] S104: Designing a maneuver controller for the satellite based on a proportional-differential controller;

[0040] S105: Design a state / bias estimator to obtain an unbiased state estimation result and a bias estimation result, and obtain an optimal state estimation value used as a posture estimation result based on the coupling relationship between the bias estimation value and the state estimation value; and use the interference term observation value obtained by the nonlinear interference observer as the unknown interference estimation result.

[0041] pass Figure 1 In the technical solution shown, this embodiment of the present invention uses the disturbance term observations obtained via a nonlinear disturbance observer as the unknown disturbance estimation result. The attitude control system model is discretized and then locally linearized. Finally, the optimal estimation of the system state is achieved through the coupling relationship between the deviation estimate and the state estimate. This achieves direct estimation of the disturbance and attitude, which is more real-time than the indirect estimation scheme of conventional solutions and is more conducive to on-orbit application.

[0042] for Figure 1In some possible implementations of the technical solution shown, constructing the satellite's attitude control system model based on the satellite's angular velocity and Euler angles in the body coordinate system includes:

[0043] The state quantity of the attitude control system of the satellite is constructed according to the angular velocity of the satellite in the body coordinate system and the corresponding Euler angle: in, Indicates the angular velocity of the satellite corresponding to the three coordinate axes in the body coordinate system; Euler angle The parameters in represent the roll angle, pitch angle and yaw angle respectively;

[0044] The satellite attitude control system model is constructed based on the attitude control system state of the satellite and the following formula as shown in Formula 1:

[0045]

[0046] Among them, C is the observation matrix and is a sixth-order unit matrix, represented by E6; u is the input; b is the deviation, T d is the known disturbance of the system; B1=J -1 , F=B; represents the angular velocity vector of the target coordinate system, and J represents the satellite's moment of inertia matrix;

[0047]

[0048] For the above technical solution, in some possible implementations, the method of designing a nonlinear disturbance observer for the attitude control system model using the constructed angular velocity channel model containing disturbance terms includes:

[0049] The angular velocity channel model including the interference term d is constructed as shown in Equation 2:

[0050]

[0051] According to the three coordinate axes corresponding to the body coordinate system, the relationship between the interference term and the deviation term is d = [d1 d2 d3] T =B1b;

[0052] set up According to the three coordinate axes corresponding to the body coordinate system, the angular velocity channel model is shown in Formula 3:

[0053]

[0054] Among them, i represents the i-th coordinate axis in the body coordinate system, B 1i is the row vector consisting of the elements of the i-th row of B1;

[0055] According to the angular velocity channel model shown in Equation 3, the observer shown in Equation 4 is designed as follows:

[0056]

[0057] Among them, sgn() is the sign function; k i1 、k i2 and k i3 Is a positive constant; the superscript ● indicates the first derivative of the variable, the superscript represents the observed value of the variable;

[0058] The error of the defined observer is set as shown in Equation 5:

[0059]

[0060] Based on Equation 5 and the relationship between the interference term and the bias term, we obtain as well as

[0061] For the angular velocity channel model shown in Formula 3, it is assumed that the interference term has a second-order derivative or the piecewise second-order derivative is differentiable and bounded, and the positive constant is determined based on the differentiability and boundedness.

[0062] For the above implementation, specifically, for the angular velocity channel model shown in Equation 3, if the interference term has a second-order derivative or is piecewise second-order differentiable and bounded, that is, Among them, ε i and is a positive number; in this case, the parameter group can be designed to satisfy:

[0063]

[0064] in, This makes the observer converge in a finite time.

[0065] For the above implementation, in some examples, the method further includes:

[0066] The observed value of the angular velocity is obtained by the nonlinear disturbance observer The observed value of the deviation and its first-order derivative and and the observed values of the interference term and its first-order derivative and

[0067] It should be noted that the observation values in the above example can be used as input data or information for the subsequent execution of step S105.

[0068] In combination with the above technical solution, in some possible implementations, discretizing the attitude control system model and obtaining a locally linearized attitude control system model based on Taylor expansion remainders includes:

[0069] According to the sampling step Δt=t k+1 -t k The discrete expression of the state quantity is determined by the discrete expression of the angular velocity observation quantity and the deviation term observation quantity as shown in Formula 6:

[0070]

[0071] Among them, the discrete expression of the angular velocity observation is recorded as The discrete expression of the deviation term observation is recorded as Represents the attitude angle estimation result at the kth moment;

[0072] According to formula 7, the discrete form model of the deviation term is determined as follows:

[0073]

[0074] Among them, p k (b k ) represents the deviation term b k The general expression of the function of ; represents zero-mean Gaussian white noise;

[0075] According to the discrete expression form of the state variable and the discrete form model of the deviation term, the discrete form of the posture control system model is constructed as shown in Formula 8:

[0076]

[0077] in, and v k are mutually uncorrelated zero-mean Gaussian white noises, and the corresponding covariance matrices are Q x , Q b and R; subscripts k and k+1 indicate adjacent sampling time numbers; T k is the known disturbance of the system T d Discrete form of C k Represents the discrete form of the observation matrix C;

[0078] exist and Nearby k (x k ) and p k (b k ) and perform Taylor expansion to obtain g k (xk ) and p k (b k ) is as follows:

[0079]

[0080]

[0081] in, and They represent Taylor expansion remainders respectively;

[0082] set up and The attitude control system model after local linearization is as follows:

[0083]

[0084] in,

[0085] In combination with the above technical solution, in some possible implementations, designing the satellite maneuver controller based on a proportional-differential controller includes:

[0086] Based on the proportional-derivative controller, the maneuvering controller is designed as shown in Equation 9:

[0087]

[0088] Among them, Φ 2,k =Φ(φ k )A bt (φ k ); Represents the discrete form of the angular velocity of the satellite in the target coordinate system; the controller parameters C1 and C2 are third-order constant diagonal matrices.

[0089] In combination with the above technical solution, in some possible implementations, the state / bias estimator is designed to obtain an unbiased state estimation result and a bias estimation result, and an optimal state estimation value used as a posture estimation result is obtained based on a coupling relationship between the bias estimation value and the state estimation value; and the interference term observation value obtained by the nonlinear interference observer is used as an unknown interference estimation result, including:

[0090] According to Equation 10, the optimal state estimator, also called the optimal estimator, is determined as:

[0091]

[0092] in, represents the optimal estimate of the state quantity, represents the covariance matrix of the state estimation error, represents the estimated value of the state quantity under the premise of no deviation, Represents the covariance matrix of the state estimation error under the premise of no bias;

[0093] According to Equation 11, the state estimator under the premise of no bias, also known as the unbiased estimator, is:

[0094]

[0095] in,

[0096]

[0097]

[0098]

[0099]

[0100]

[0101] use represents the estimated value of the deviation, The covariance matrix of the deviation estimation error is represented by ; the deviation estimator, also called the deviation estimator, is determined according to formula 12, which is:

[0102]

[0103] in: E3 represents a 3rd order unit matrix;

[0104] According to the coupling relationship between the deviation estimation value and the state estimation value shown in Equation 13 and Equations 10, 11, and 12, the optimal state estimation result including the attitude angular velocity and Euler angle is obtained

[0105]

[0106] The disturbance term observation value obtained by the nonlinear disturbance observer is used as the unknown disturbance estimation result.

[0107] It should be noted that the embodiment of the present invention also demonstrates the effect of the above technical solution through simulation experiments. The simulation experiment conditions and prerequisites are as follows:

[0108] Set the unknown interference amount in the x channel to The known interference is Where A0 = 1.5 × 10 -5 Nm, ω0 = 0.001 rad / s.

[0109] The standard deviations of attitude angle and angular velocity measurement noise are: φ =0.002deg and σ ω =0.0002deg / s; Satellite moment of inertia J = diag([17 12 10])kgm 2 When a flywheel is used as the actuator, its maximum angular momentum is 2 Nms and its maximum output torque is 0.2 Nm. E3 represents the third-order identity matrix. Controller parameters C1 = 0.54E3 and C2 = 0.11E3.

[0110] The initial values and related parameters of the observer are: k i3 =1.1μ i , μ1=5×10 -3 , μ2=μ3=5×10 -4 .

[0111] The initial values and parameters of the filter are: β0=0 6×3 , Q b =(1×10 -3 ) 2 E3, σ ω =1×10 -5 rad / s, σ φ =1×10 -4 rad.

[0112] Based on the above simulation parameters, the simulation is processed using the aforementioned technical solution, and the resulting simulation diagram is shown below.

[0113] Figure 2 A schematic diagram of unknown interference observation results using the technical solution of an embodiment of the present invention is shown. It can be seen from the figure that the difference between the observed value of the interference term and the set value is within 0.002Nm. Figure 3 The optimal estimation result of the attitude angular velocity using the technical solution of the embodiment of the present invention is shown. It can be seen from the figure that the state value, observation value and optimal estimation value (also called filtered value in the figure) of the attitude angular velocity almost coincide with each other. Figure 4 The figure shows the optimal estimation result of the Euler angle using the technical solution of the embodiment of the present invention. It can be seen from the figure that the filtered value is more consistent with the state value than the observed value, that is, the optimal estimation result is significantly better than the observed value of the observer. Figure 5 The error between the observed and estimated values of the attitude angular velocity is shown in the figure. It can be seen from the figure that the two errors are very close, both within 2×10-4 Within deg / s. Figure 6 The error diagram of the observed and estimated values of the attitude angle is shown. It can be seen from the figure that the filtering error of the estimated value is more stable than the observation error, and the result is better. Figure 7 The error between the observed value and the state value of the unknown interference is shown in the figure. It can be seen from the figure that the observed value will have multiple peaks, thus forming the outlier effect.

[0114] pass Figures 2 to 7 It can be seen from the simulation results that the estimation error value of the technical solution of the embodiment of the present invention is small, and has higher estimation accuracy and precision than the observed value.

[0115] Based on the same inventive concept as the above technical solution, see Figure 8 , which shows an apparatus 80 for estimating unknown interference and attitude during satellite maneuvers provided by an embodiment of the present invention, the apparatus 80 includes: a system model building part 801, an observer design part 802, a discretization part 803, a controller design part 804 and an estimation part 805; wherein,

[0116] The system model building part 801 is configured to build an attitude control system model of the satellite based on the angular velocity and Euler angle of the satellite in the body coordinate system;

[0117] The observer design part 802 is configured to design a nonlinear disturbance observer for the attitude control system model using the constructed angular velocity channel model including the disturbance term;

[0118] The discretization part 803 is configured to discretize the attitude control system model and obtain a locally linearized attitude control system model according to Taylor expansion remainders;

[0119] The controller design part 804 is configured to design a maneuver controller for the satellite based on a proportional-derivative controller;

[0120] The estimation part 805 is configured to obtain an unbiased state estimation result and a bias estimation result under the estimation of the state / bias estimator, and obtain an optimal state estimation value used as a posture estimation result based on the coupling relationship between the bias estimation value and the state estimation value; and use the interference term observation value obtained by the nonlinear interference observer as the unknown interference estimation result.

[0121] It should be noted that for Figure 8 The device 80 for estimating unknown interference and attitude during satellite maneuvering is shown, and each part corresponds to Figure 1Therefore, for the details of the parts of the device 80 that are not described in detail, please refer to the description of the technical solution of the unknown interference and attitude estimation method during the satellite maneuvering process. This embodiment of the present invention will not be described in detail.

[0122] It can be understood that in this embodiment, "part" can be part of a circuit, part of a processor, part of a program or software, etc., and of course it can also be a unit, a module, or a non-modular one.

[0123] In addition, the components in this embodiment may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The above-mentioned integrated units may be implemented in the form of hardware or software functional modules.

[0124] If the integrated unit is implemented as a software functional module and is not sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this embodiment, or the portion that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute all or part of the steps of the method described in this embodiment. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0125] Therefore, this embodiment provides a computer storage medium, which stores a program for estimating unknown interference and attitude during satellite maneuvers. When the program for estimating unknown interference and attitude during satellite maneuvers is executed by at least one processor, the steps of the method for estimating unknown interference and attitude during satellite maneuvers described in the above technical solution are implemented.

[0126] According to the device 80 and computer storage medium for estimating unknown interference and attitude during the above-mentioned satellite maneuvering process, see Figure 9, which shows the specific hardware structure of a computing device 90 of an apparatus 80 capable of implementing the above-mentioned unknown interference and attitude estimation during satellite maneuvers provided by an embodiment of the present invention. The computing device 90 can be a wireless device, a mobile or cellular phone (including a so-called smart phone), a personal digital assistant (PDA), a video game console (including a video display, a mobile video game device, a mobile video conferencing unit), a laptop computer, a desktop computer, a TV set-top box, a tablet computing device, an e-book reader, a fixed or mobile media player, etc. The computing device 90 includes: a communication interface 901, a memory 902 and a processor 903; the various components are coupled together through a bus system 904. It can be understood that the bus system 904 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 904 also includes a power bus, a control bus and a status signal bus. However, for the sake of clarity, in Figure 9 In FIG, various buses are labeled as bus system 904.

[0127] The communication interface 901 is used to receive and send signals during the process of sending and receiving information with other external network elements;

[0128] The memory 902 is used to store computer programs that can be run on the processor 903;

[0129] The processor 903 is used to execute the steps of the unknown interference and attitude estimation method during satellite maneuvering described in the aforementioned technical solution when running the computer program, which will not be described in detail here.

[0130] It is understood that the memory 902 in the embodiment of the present invention can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct RAM bus random access memory (DRRAM). The memory 902 of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0131] Processor 903 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by hardware integrated logic circuits or software instructions in processor 903. The above processor 903 may be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in conjunction with the embodiments of the present invention can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in memory 902, and processor 903 reads information from memory 902 and, in conjunction with its hardware, completes the steps of the above method.

[0132] It is understood that the embodiments described herein may be implemented using hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit may be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described herein, or a combination thereof.

[0133] For software implementation, the techniques described herein can be implemented by modules (e.g., procedures, functions, etc.) that perform the functions described herein. The software code can be stored in a memory and executed by a processor. The memory can be implemented in the processor or external to the processor.

[0134] It should be noted that the technical solutions described in the embodiments of the present invention can be arbitrarily combined without conflict.

[0135] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A method for estimating unknown interference and attitude during satellite maneuvers, characterized in that: The method comprises: Constructing an attitude control system model of the satellite based on the angular velocity and Euler angle of the satellite in the body coordinate system; Designing a nonlinear disturbance observer for the attitude control system model using the constructed angular velocity channel model including disturbance terms; Discretizing the attitude control system model and obtaining a locally linearized attitude control system model based on Taylor expansion remainders; Designing a maneuver controller for the satellite based on a proportional-derivative controller; Designing a state / bias estimator to obtain an unbiased state estimation result and a bias estimation result, and obtaining an optimal state estimation value used as a posture estimation result based on a coupling relationship between the bias estimation value and the state estimation value; and using the interference term observation value obtained by the nonlinear interference observer as an unknown interference estimation result; The method of constructing the satellite's attitude control system model based on the satellite's angular velocity and Euler angle in the body coordinate system includes: The state quantity of the attitude control system of the satellite is constructed according to the angular velocity of the satellite in the body coordinate system and the corresponding Euler angle: ;in, Indicates the angular velocity of the satellite corresponding to the three coordinate axes in the body coordinate system; Euler angle The parameters in represent the roll angle, pitch angle and yaw angle respectively; The satellite attitude control system model is constructed based on the attitude control system state of the satellite and the following formula as shown in Formula 1: （1） in, C is the observation matrix and is a sixth-order identity matrix, express; u is the input quantity; b is the deviation, T d is the known disturbance of the system; , ; ; , ; ; represents the angular velocity vector of the target coordinate system, J represents the satellite's moment of inertia matrix; Discretizing the attitude control system model and obtaining a locally linearized attitude control system model according to Taylor expansion remainders includes: According to the sampling step The discrete expression of the state quantity is determined by the discrete expression of the angular velocity observation quantity and the deviation term observation quantity as shown in Formula 6: （6） Among them, the discrete expression of the angular velocity observation is recorded as ; The discrete expression of the deviation term observation is recorded as ; Indicates the k The attitude angle estimation result at the moment; According to formula 7, the discrete form model of the deviation term is determined as follows: （7） in, Represents the deviation term The general expression of the function of ; represents zero-mean Gaussian white noise; According to the discrete expression form of the state quantity and the discrete form model of the deviation term, the discrete form of the posture control system model is constructed as shown in Formula 8: （8） in, 、 and are mutually uncorrelated zero-mean Gaussian white noises, and the corresponding covariance matrices are 、 and ; Subscript k and k +1 indicates the adjacent sampling time labels; T k is the known disturbance of the system T d Discrete form of C k Represents the observation matrix C Discrete form of exist and Nearby and Perform Taylor expansion and get and The Taylor expansion of is as follows: in, and They represent Taylor expansion remainders respectively; set up and , then the attitude control system model after local linearization is as follows: in, , ; The design of a state / bias estimator obtains an unbiased state estimation result and a bias estimation result, and obtains an optimal state estimation value used as a posture estimation result based on a coupling relationship between the bias estimation value and the state estimation value; and uses the interference term observation value obtained by the nonlinear interference observer as an unknown interference estimation result, including: According to formula 10, the optimal state estimator is determined as: （10） in, represents the optimal estimate of the state quantity, represents the covariance matrix of the state estimation error, represents the estimated value of the state quantity under the premise of no deviation, Represents the covariance matrix of the state estimation error under the premise of no bias; According to formula 11, the state estimator under the premise of no deviation is: （11） in, use represents the estimated value of the deviation, The covariance matrix of the deviation estimation error is represented by: （12） in: ; ; ; ; Represents a 3rd-order unit matrix; According to the coupling relationship between the deviation estimation value and the state estimation value shown in Equation 13 and Equations 10, 11, and 12, the optimal state estimation result including the attitude angular velocity and Euler angle is obtained ; （13） The disturbance term observation value obtained by the nonlinear disturbance observer is used as the unknown disturbance estimation result.

2. The method according to claim 1, characterized in that The method of designing a nonlinear disturbance observer for the attitude control system model using the constructed angular velocity channel model containing disturbance terms includes: Constructing interference d The angular velocity channel model is shown in Equation 2: （2） Among them, according to the three coordinate axes corresponding to the body coordinate system, the relationship between the interference term and the deviation term is: ; set up , according to the three coordinate axes corresponding to the body coordinate system, the angular velocity channel model is shown in Formula 3: （3） in, i Indicates the first i coordinate axes, yes No. i A row vector consisting of row elements; According to the angular velocity channel model shown in Equation 3, the observer shown in Equation 4 is designed as follows: （4） Among them, sgn() is the sign function; 、 and is a positive constant; the superscript ● indicates the first-order derivative of the variable, and the superscript ︶ indicates the observed value of the variable; The error of the defined observer is set as shown in Equation 5: （5） Based on Equation 5 and the relationship between the interference term and the bias term, we obtain as well as ; For the angular velocity channel model shown in Formula 3, it is assumed that the interference term has a second-order derivative or the piecewise second-order derivative is differentiable and bounded, and the positive constant is determined based on the differentiability and boundedness.

3. The method according to claim 2, characterized in that The method further comprises: The observed value of the angular velocity is obtained by the nonlinear disturbance observer , the observed value of the deviation and its first-order derivative and , and the observed values of the interference term and its first-order derivative and .

4. The method according to claim 3, characterized in that The method of designing a maneuvering controller of the satellite based on a proportional-differential controller includes: Based on the proportional-derivative controller, the maneuvering controller is designed as shown in Equation 9: （9） in, ; ; The discrete form of the satellite's angular velocity in the target coordinate system; the controller parameter C 1. C 2 is a third-order constant diagonal matrix.

5. A device for estimating unknown interference and attitude during satellite maneuvers, characterized in that: The device includes: a system model building part, an observer design part, a discretization part, a controller design part and an estimation part; wherein, The system model building part is configured to build an attitude control system model of the satellite based on the angular velocity and Euler angle of the satellite in the body coordinate system; The observer design part is configured to design a nonlinear disturbance observer for the attitude control system model using the constructed angular velocity channel model including the disturbance term; The discretization part is configured to discretize the attitude control system model and obtain a locally linearized attitude control system model according to Taylor expansion remainders; The controller design part is configured to design a maneuver controller of the satellite based on a proportional-derivative controller; The estimation part is configured to obtain an unbiased state estimation result and a bias estimation result under the estimation of the state / bias estimator, and obtain an optimal state estimation value used as a posture estimation result based on a coupling relationship between the bias estimation value and the state estimation value; and use the interference term observation value obtained by the nonlinear interference observer as the unknown interference estimation result; The system model construction part is configured to construct the attitude control system state quantity of the satellite according to the angular velocity of the satellite in the body coordinate system and the corresponding Euler angle: ;in, Indicates the angular velocity of the satellite corresponding to the three coordinate axes in the body coordinate system; Euler angle The parameters in represent the roll angle, pitch angle and yaw angle respectively; The satellite attitude control system model is constructed based on the attitude control system state of the satellite and the following formula as shown in Formula 1: （1） in, C is the observation matrix and is a sixth-order identity matrix, express; u is the input quantity; b is the deviation, T d is the known disturbance of the system; , ; ; , ; ; represents the angular velocity vector of the target coordinate system, J represents the satellite's moment of inertia matrix; The discretization part is configured to be based on the sampling step size The discrete expression of the state quantity is determined by the discrete expression of the angular velocity observation quantity and the deviation term observation quantity as shown in Formula 6: （6） Among them, the discrete expression of the angular velocity observation is recorded as ; The discrete expression of the deviation term observation is recorded as ; Indicates the k The attitude angle estimation result at the moment; According to formula 7, the discrete form model of the deviation term is determined as follows: （7） in, Represents the deviation term The general expression of the function of ; represents zero-mean Gaussian white noise; According to the discrete expression form of the state quantity and the discrete form model of the deviation term, the discrete form of the posture control system model is constructed as shown in Formula 8: （8） in, 、 and are mutually uncorrelated zero-mean Gaussian white noises, and the corresponding covariance matrices are 、 and ; Subscript k and k +1 indicates the adjacent sampling time labels; T k is the known disturbance of the system T d Discrete form of C k Represents the observation matrix C Discrete form of exist and Nearby and Perform Taylor expansion and get and The Taylor expansion of is as follows: in, and They represent Taylor expansion remainders respectively; set up and , then the attitude control system model after local linearization is as follows: in, , ; The estimation part is configured to determine the optimal state estimator according to equation 10: （10） in, represents the optimal estimate of the state quantity, represents the covariance matrix of the state estimation error, represents the estimated value of the state quantity under the premise of no deviation, Represents the covariance matrix of the state estimation error under the premise of no bias; According to formula 11, the state estimator under the premise of no deviation is: （11） in, use represents the estimated value of the deviation, The covariance matrix of the deviation estimation error is represented by: （12） in: ; ; ; ; represents a 3rd-order unit matrix; According to the coupling relationship between the deviation estimation value and the state estimation value shown in Equation 13 and Equations 10, 11, and 12, the optimal state estimation result including the attitude angular velocity and Euler angle is obtained ; （13） The disturbance term observation value obtained by the nonlinear disturbance observer is used as the unknown disturbance estimation result.

6. A computing device, characterized in that The computing device includes: a communication interface, a memory and a processor; each component is coupled together through a bus system, wherein, The communication interface is used to receive and send signals when sending and receiving information with other external network elements; The memory is used to store a computer program that can be run on the processor; The processor is configured to execute the steps of the method for estimating unknown interference and attitude during satellite maneuvers as described in any one of claims 1 to 4 when running the computer program.

7. A computer storage medium, characterized in that The computer storage medium stores a program for estimating unknown interference and attitude during satellite maneuvers. When the program for estimating unknown interference and attitude during satellite maneuvers is executed by at least one processor, the steps of the method for estimating unknown interference and attitude during satellite maneuvers according to any one of claims 1 to 4 are implemented.

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