On-orbit calibration method and device for centroid offset of inertial sensor

Abstract

The invention relates to the technical field of data processing, and discloses an inertial sensor centroid offset on-orbit calibration method and device. The method comprises the following steps: acquiring an angular velocity and an angular acceleration of the spacecraft after maneuvering through the inertial sensor; constructing a measurement observation model by using the angular velocity of the spacecraft and the angular acceleration; processing the measurement observation model through a pre-constructed Kalman filter to obtain an estimated mass center offset; and calculating based on the estimated mass center offset and the acceleration output by the inertial sensor to obtain a calibration result of mass center offset between the mass center of the inertial sensor and the gravity center of the spacecraft. Through the above steps, the calibration of the centroid offset can be realized in the short-period maneuver of the spacecraft. Through one-time maneuvering, centroid offset and other parameters needing on-orbit calibration are calibrated at the same time, and the maneuvering cost is reduced.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and in particular to an on-orbit calibration method and device for an inertial sensor mass center offset. Background Art

[0002] Traditional parameter calibration methods have been widely used in previous work, but for new scientific missions and design layouts of some special spacecraft, traditional methods are no longer applicable. Recently, the method of GRACE satellite center of mass calibration is to apply appropriate periodic magnetic torque to the satellite to drive the satellite without the help of thruster torque, obtain the attitude quaternion simulation data simulated by the accelerometer and the magnetometer data, and then use the minimum variance estimation algorithm for data processing. Different from previous related work, due to the long distance from the earth, some special spacecraft cannot use the earth's magnetic field to drive the magnetic torquer, and the environmental noise they face also needs to be re-evaluated. Summary of the invention

[0003] In view of this, an embodiment of the present invention provides an on-orbit calibration method and device for an inertial sensor center of mass offset, so as to solve the problem that the traditional parameter calibration method is no longer applicable to the new scientific missions and design layouts of some special spacecraft.

[0004] In a first aspect, an embodiment of the present invention provides an on-orbit calibration method for an inertial sensor mass center offset, wherein the inertial sensor is disposed on a spacecraft, and the method comprises: angular velocity and angular acceleration of the spacecraft after the maneuver by the inertial sensor; constructing a metrological observation model using the angular velocity of the spacecraft and the angular acceleration; The measurement observation model is processed by a pre-constructed Kalman filter to obtain an estimated center of mass offset; Based on the estimated center of mass offset and the acceleration calculation output by the inertial sensor, a calibration result of the center of mass offset between the center of mass of the inertial sensor and the center of gravity of the spacecraft is obtained.

[0005] In an embodiment of the present application, the angular velocity and angular acceleration after the spacecraft maneuvers by the inertial sensor include: Detecting an attitude signal of test quality generated by an inertial sensor, wherein the attitude signal is generated by the inertial sensor after the spacecraft maneuvers; The attitude signal is analyzed to obtain the angular velocity and angular acceleration of the spacecraft.

[0006] In the embodiment of the present application, the metrology observation model is as follows:

[0007] in, , The linear term of acceleration as a non-conservative force coupled with the test mass can be treated by eliminating the linear trend.

[0008] In the embodiment of the present application, the measurement observation model is processed by a pre-constructed Kalman filter to obtain an estimated centroid shift, including: Acquiring operating parameters of a Kalman filter and determining an update equation of the Kalman filter, wherein the operating parameters include state variables, an initial state estimate, and a covariance matrix; Preprocessing the angular velocity and the angular acceleration to obtain processed angular velocity and angular acceleration; Initialize the state variables and covariance matrix of the Kalman filter, and use the initialized state variables and system model to perform predictions to obtain prediction results; Comparing the preprocessed angular velocity and angular acceleration with the prediction result to obtain a comparison result, and calculating the Kalman gain using the comparison result; Calculating updated values ​​of state variables and updated values ​​of covariance matrix using the Kalman gain and the update equation; An estimated center of mass shift is determined based on the updated values ​​of the state variables and the updated values ​​of the covariance matrix.

[0009] In the embodiment of the present application, the formula of the Kalman filter is as follows:

[0010]

[0011] is the state transfer matrix in the prediction process, is the gain of input U, W is the estimated process noise, and V is the measurement noise, where the measured value Y, the estimated , the observation matrix H, the observation matrix H is:

[0012]

[0013] .

[0014] In an embodiment of the present application, the calibration result of the center of mass offset between the center of mass of the inertial sensor and the center of gravity of the spacecraft is obtained based on the estimated center of mass offset and the acceleration calculation output by the inertial sensor, including: Obtaining the acceleration actually output by the inertial sensor at present; Performing a delinearization trend processing on the acceleration to obtain a processed acceleration; Obtaining the linear acceleration caused by the estimated center of mass deviation; determining a difference between the processed acceleration and the linear acceleration, and determining an actual value of the center of mass offset based on the difference; A calibration result of the mass center offset between the mass center of the inertial sensor and the center of gravity of the spacecraft is determined according to the actual value of the mass center offset.

[0015] In an embodiment of the present application, the method further includes: Collecting acceleration data output by the inertial sensor, and analyzing the acceleration data to obtain a noise analysis result; Determining an acceleration noise term coupled with the mass center offset according to the calibration result of the mass center offset and the noise analysis result; The acceleration noise item in the acceleration data is eliminated or reduced to obtain processed acceleration data, and the acceleration noise level corresponding to the processed acceleration data is evaluated; if the acceleration noise level meets a preset condition, the processed acceleration data is used as output.

[0016] In a second aspect, an embodiment of the present invention provides an on-orbit calibration device for an inertial sensor mass center offset, the device comprising: An acquisition module, used for obtaining the angular velocity and angular acceleration of the spacecraft after the maneuver occurs through the inertial sensor; A construction module, used to construct a metrology observation model using the angular velocity of the spacecraft and the angular acceleration; A processing module, used for processing the metrology observation model through a pre-built Kalman filter to obtain an estimated centroid offset; The calibration module is used to obtain a calibration result of the center of mass offset between the center of mass of the inertial sensor and the center of gravity of the spacecraft based on the estimated center of mass offset and the acceleration calculation output by the inertial sensor.

[0017] In a third aspect, an embodiment of the present invention provides an electronic device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, computer instructions being stored in the memory, and the processor executing the method of the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0018] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method of the first aspect or any corresponding embodiment thereof.

[0019] In the embodiment of the present application, the inertial sensor can generally measure the angular velocity and angular acceleration of the spacecraft in different axial directions. These measurements provide the rotational motion information of the spacecraft. Based on the kinematic principle of the spacecraft, the angular velocity and angular acceleration can be linked to the attitude change of the spacecraft, and the angular velocity and angular acceleration are used as input to construct a metrological observation model to describe the attitude motion of the spacecraft. The Kalman filter processes the output of the metrological observation model to estimate the center of mass offset. Then the Kalman filter uses the previous estimated value and the current measured value to continuously update and optimize the estimate of the center of mass offset. Through filtering, the influence of measurement noise and uncertainty can be reduced and the accuracy of the estimate can be improved. Finally, the estimated center of mass offset is combined with the acceleration output by the inertial sensor, and the center of mass offset between the center of mass of the inertial sensor and the center of gravity of the spacecraft can be further calculated. This calibration result can be used in subsequent navigation and control systems to improve the accuracy and stability of the attitude control of the spacecraft. Through the above steps, the calibration of the center of mass offset can be achieved within the short-period maneuver of the spacecraft. Through one maneuver, the center of mass offset and other parameters that need to be calibrated on orbit are calibrated at the same time, reducing the maneuvering cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0021] Figure 1 is a flow chart of an on-orbit calibration method for an inertial sensor center of mass offset according to some embodiments of the present invention; Figure 2 is a schematic diagram of an overall torque signal according to some embodiments of the present invention; Figure 3 is a schematic diagram of a measurement signal corresponding to an angular velocity according to some embodiments of the present invention; Figure 4 is a schematic diagram of a measurement signal corresponding to an angular acceleration according to some embodiments of the present invention; Figure 5 is a schematic diagram of estimating centroid shift according to a Kalman filter of some embodiments of the present invention; Figure 6 is a schematic diagram of comparison between centroid offset calibration and true value according to some embodiments of the present invention; Figure 7 is a structural block diagram of an on-orbit calibration device for an inertial sensor mass center offset according to an embodiment of the present invention; Figure 8It is a schematic diagram of the hardware structure of the electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0023] According to an embodiment of the present invention, a method and apparatus for on-orbit calibration of an inertial sensor center of mass offset are provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in an order different from that shown here.

[0024] In this embodiment, a method for on-orbit calibration of the center of mass offset of an inertial sensor is provided. Figure 1 FIG. 1 is a flow chart of an on-orbit calibration method for an inertial sensor center of mass offset according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps: Step S11, using inertial sensors to measure the angular velocity and angular acceleration of the spacecraft after the maneuver.

[0025] The spacecraft in the embodiment of the present application is the Taiji-2 satellite. Since the Taiji-2 satellite cannot use the earth's magnetic field to drive the magnetic torquer, the environmental noise it faces also needs to be reconsidered. In terms of accuracy requirements, the acceleration noise index of Taiji-2 is 10 -14 ms -2 / Hz 1 / 2 The magnitude is much higher than Tai Chi No. 1 3 10 -9 ms -2 / Hz 1 / 2 The Taiji-2 satellite adopts a new design layout, with two inertial sensor systems on each satellite. Therefore, under ideal conditions, there is a deviation of about 0.1 m in the sensitive axis direction between the center of mass of the test mass and the center of mass of the satellite. Therefore, this application provides an on-orbit parameter calibration scheme for the Taiji-2 inertial sensor.

[0026] In an embodiment of the present application, the angular velocity and angular acceleration of the spacecraft after the maneuver is determined by an inertial sensor, including: detecting an attitude signal of a test quality generated by the inertial sensor, wherein the attitude signal is generated by the inertial sensor after the spacecraft maneuvers; and analyzing the attitude signal to obtain the angular velocity and angular acceleration of the spacecraft.

[0027] Specifically, since Taiji-2 has two inertial sensor systems, the test mass block in each inertial sensor system and the satellite center are designed to have a deviation of 0.1m in the sensitive axis direction. Due to the existence of the electrostatic suspension system, the test mass and the spacecraft perform synchronous attitude motion, so the angular velocity and angular acceleration of the test mass also produce attitude motions of the same magnitude as the angular velocity and angular acceleration of the spacecraft. Through a maneuver of the satellite, the front-end electronic model of the inertial sensor records the attitude signal of the test mass. By analyzing these signals, the angular velocity and angular acceleration of the spacecraft can be obtained. For example, by processing and analyzing the data measured by the accelerometer and gyroscope, the angular velocity and angular acceleration of the spacecraft can be calculated.

[0028] It is worth mentioning that the Taiji Project plans to have three satellites form an equilateral triangle gravitational wave detection constellation to orbit the sun at an orbit of about 50 million kilometers from the earth. Due to the long distance from the earth, the earth's magnetic field cannot be used to drive the magnetic torquer, so three sets of microthrusters are used to drive a single satellite. The thrust range of the microthruster is 2 to 100 micronewtons, with a thrust resolution of 0.1 micronewtons. According to the law of rigid body rotation, it can generate a torque of about 10 to the negative 6th power Newton-meter to 10 to the negative 4th power Newton-meter.

[0029] Step S12, constructing a metrological observation model using the angular velocity and angular acceleration of the spacecraft.

[0030] In the embodiment of the present application, the measurement observation model is as follows: .

[0031] in: , The linear term of acceleration as a non-conservative force coupled with the test mass can be treated by eliminating the linear trend.

[0032] It should be noted that the attitude motion of the spacecraft will be determined by the center of mass offset vector The test mass is subjected to a coupled acceleration, which can be expressed as: .

[0033] At this time, the actual output acceleration of the inertial sensor is: .

[0034] in, This is the gravitational gradient acceleration experienced by the satellite. Since Taiji-2 orbits the sun at a great distance from the Earth, the accelerometer measurement model ignores disturbances caused by solid Earth tides, ocean tides, etc. The non-conservative force acceleration of the test mass, including atmospheric drag, solar pressure, and earth radiation pressure, can be approximated by a linear function of time. The above gives the components of the linear acceleration of the test mass when the center of mass offset exists. The accelerometer observation model can be simplified to: .

[0035] Step S13, processing the metrology observation model through a pre-built Kalman filter to obtain an estimated center of mass offset.

[0036] In an embodiment of the present application, the metrology observation model is processed by a pre-constructed Kalman filter to obtain an estimated center of mass offset, including: obtaining working parameters of the Kalman filter and determining a Kalman filter update equation, wherein the working parameters include state variables, an initial state estimate, and a covariance matrix; pre-processing the angular velocity and angular acceleration to obtain processed angular velocity and angular acceleration; initializing the state variables and covariance matrix of the Kalman filter, and using the initialized state variables and the system model to perform predictions to obtain prediction results; comparing the pre-processed angular velocity and angular acceleration with the prediction results to obtain comparison results, and using the comparison results to calculate the Kalman gain; using the Kalman gain and the update equation to calculate the updated values ​​of the state variables and the updated values ​​of the covariance matrix; and determining the estimated center of mass offset based on the updated values ​​of the state variables and the updated values ​​of the covariance matrix.

[0037] It should be noted that after obtaining the satellite angular velocity and angular acceleration signals, a Kalman filter is constructed to calibrate the center of mass offset: .

[0038] .

[0039] is the state transfer matrix in the prediction process, is the gain of input U, W is the estimated process noise, and V is the measurement noise, where the measured value Y, the estimated , the observation matrix H, the observation matrix H is: .

[0040] .

[0041]

[0042] Because the center of mass shift has no dynamic characteristics, , .

[0043] Posterior estimate: .

[0044] Specifically, first, initialize the working parameters of the Kalman filter, select appropriate state variables to describe the system, such as modeling angular velocity and angular acceleration, which can be selected as state variables. Estimate the initial state of the system, such as the initial angular velocity and initial angular acceleration. Initialize the covariance matrix, which represents the uncertainty of the state variables. Secondly, pre-process the angular velocity and angular acceleration, such as removing noise, filtering and other operations, to obtain the processed angular velocity and angular acceleration. At the same time, the initial state estimate is used as the state variable of the Kalman filter. Initialize the covariance matrix to an appropriate value.

[0045] Then, use the initialized state variables and system model to make predictions, that is, use the current state variables to predict the state at the next moment according to the system model. Calculate the covariance matrix of the prediction results. Calculate the difference between the preprocessed angular velocity and angular acceleration and the prediction results. Use the comparison results to calculate the Kalman gain, Kalman gain: .

[0046] Finally, the Kalman gain and update equation are used to calculate the updated values ​​of the state variables and the updated values ​​of the covariance matrix, and the estimated center of mass offset is determined based on the updated values ​​of the state variables and the updated values ​​of the covariance matrix. Update the error covariance matrix: .

[0047] Step S14, based on the estimated center of mass offset and the acceleration calculation output by the inertial sensor, a calibration result of the center of mass offset between the center of mass of the inertial sensor and the center of gravity of the spacecraft is obtained.

[0048] In an embodiment of the present application, a calibration result of the center of mass offset between the center of mass of the inertial sensor and the center of gravity of the spacecraft is obtained based on the estimated center of mass offset and the acceleration calculation output by the inertial sensor, including: obtaining the acceleration currently actually output by the inertial sensor; performing delinearization trend processing on the acceleration to obtain the processed acceleration; obtaining the linear acceleration caused by the estimated center of mass offset; determining the difference between the processed acceleration and the linear acceleration, and determining the actual value of the center of mass offset based on the difference; and determining the calibration result of the center of mass offset between the center of mass of the inertial sensor and the center of gravity of the spacecraft based on the actual value of the center of mass offset.

[0049] Specifically, multiple inertial sensors are installed on the structure of the spacecraft to ensure that the three components of acceleration can be measured. Determine the reference coordinate system and inertial characteristics of the spacecraft. Use the inertial sensor to measure the acceleration of the structure and record the measurement data. These data will serve as the basis for subsequent analysis. Obtain the acceleration data actually output by the current inertial sensor. Then delinearize the acceleration data to remove the linear trend caused by gravity and other external forces to obtain more accurate acceleration data. Use low-pass filtering, high-pass filtering or other appropriate filtering techniques to filter the acceleration data. According to the design model of the spacecraft, analyze the possible offset of the center of mass, and combine the mass distribution, rotational inertia and other information to generate a model for estimating the acceleration of the center of mass offset. Then use mathematical modeling, finite element analysis or other methods to calculate the acceleration data caused by the estimated center of mass offset. And calculate the difference between the accelerations based on the processed acceleration data and the estimated center of mass offset acceleration.

[0050] Finally, the acceleration difference is analyzed and processed using the improved least squares method or other appropriate algorithms, and the processing results are stored in variables. By calculating the difference value, the actual value of the center of mass offset can be obtained and aligned with the reference coordinate system.

[0051] In an embodiment of the present application, the method also includes: collecting acceleration data output by the inertial sensor, and analyzing the acceleration data to obtain a noise analysis result; determining the acceleration noise term coupled with the center of mass offset according to the calibration result of the center of mass offset and the noise analysis result; eliminating or reducing the acceleration noise term in the acceleration data to obtain processed acceleration data, and evaluating the acceleration noise level corresponding to the processed acceleration data; if the acceleration noise level meets the preset conditions, the processed acceleration data is used as output.

[0052] Specifically, after the acceleration data is collected, it needs to be analyzed to determine the characteristics and level of the noise. This can be achieved by using various noise analysis techniques, such as time domain analysis, frequency domain analysis, or statistical analysis. The results of the noise analysis will help understand information such as the type, amplitude, and frequency distribution of the noise. Because in some cases, the center of mass offset may cause additional acceleration noise. By calibrating the center of mass offset and combining the noise analysis results, the acceleration noise terms related to the center of mass offset can be determined. These noise terms may be caused by mechanical vibration, friction, or other factors caused by the center of mass offset. When the acceleration noise terms coupled with the center of mass offset are determined, appropriate measures can be taken to eliminate or reduce these noises. Including the use of filtering technology, digital signal processing algorithms or other noise elimination methods. By processing the acceleration data, the impact of noise on the data can be reduced or eliminated, and the quality and accuracy of the data can be improved.

[0053] After noise elimination or reduction processing, processed acceleration data is obtained. At this point, the processed acceleration noise level needs to be evaluated to determine whether it meets the preset conditions. Various evaluation indicators such as noise root mean square (RMS), signal-to-noise ratio (SNR) or other related indicators can be used to evaluate the noise level. If the processed acceleration noise level meets the preset conditions, then the data can be considered reliable and can be used as output for subsequent applications or analysis. If the noise level does not meet the conditions, it may be necessary to further optimize the processing method or re-evaluate the performance of the system.

[0054] In the embodiment of the present application, the inertial sensor can generally measure the angular velocity and angular acceleration of the spacecraft in different axial directions. These measurements provide the rotational motion information of the spacecraft. Based on the kinematic principle of the spacecraft, the angular velocity and angular acceleration can be linked to the attitude change of the spacecraft, and the angular velocity and angular acceleration are used as input to construct a metrological observation model to describe the attitude motion of the spacecraft. The Kalman filter processes the output of the metrological observation model to estimate the center of mass offset. Then the Kalman filter uses the previous estimated value and the current measured value to continuously update and optimize the estimate of the center of mass offset. Through filtering, the influence of measurement noise and uncertainty can be reduced and the accuracy of the estimate can be improved. Finally, the estimated center of mass offset is combined with the acceleration output by the inertial sensor, and the center of mass offset between the center of mass of the inertial sensor and the center of gravity of the spacecraft can be further calculated. This calibration result can be used in subsequent navigation and control systems to improve the accuracy and stability of the attitude control of the spacecraft. Through the above steps, the calibration of the center of mass offset can be achieved within the short-period maneuver of the spacecraft. Through one maneuver, the center of mass offset and other parameters that need to be calibrated on orbit are calibrated at the same time, reducing the maneuvering cost.

[0055] The following is a complete example. Using the short-period maneuver of the satellite (the maneuver duration is 250s), the micro-thruster of Taiji-2 swings the satellite to produce: an amplitude of 10 -6 The square wave attitude maneuvering signal of the N·m level simulates the ringing phenomenon of the signal transient transition caused by the impedance mismatch of the transmission line. In the space environment, the noise amplitude of the micro-thruster in the measurement frequency band is expected to be 10 - 7 N·m level, so that the amplitude and duty cycle of the signal have a slight jitter, plus a slight line drift and slope to simulate the instability caused by the fuel supply and control system errors during the micro-thruster maneuver. Based on this, the dynamic equation of satellite maneuvers is substituted to obtain the overall torque signal as follows: Figure 2 shown.

[0056] It should be noted that the overall torque signal is used to simulate the total torque generated when the satellite maneuvers. It mainly considers the swing of the micro-thruster and the noise and instability associated with it. This signal is mainly used to analyze and study the dynamic characteristics of the satellite during maneuvers. When the satellite maneuvers, the overall torque signal will affect the attitude of the satellite. The inertial sensor can sense the attitude changes of the satellite and generate corresponding attitude signals.

[0057] Then the angular velocity is determined based on the attitude signal of the inertial sensor (such as Figure 3 shown) and angular acceleration ( Figure 4 As shown in Figure 2), the inertial sensors will measure the angular velocity of the satellite platform. , angular acceleration , and construct the accelerometer observation model.

[0058] After obtaining the satellite angular velocity and angular acceleration signals, a Kalman filter is constructed to calibrate the center of mass offset: .

[0059] .

[0060] is the state transfer matrix in the prediction process, is the gain of input U, W is the estimated process noise, and V is the measurement noise, where the measured value Y, the estimated , the observation matrix H, the observation matrix H is:

[0061]

[0062]

[0063] Because the center of mass shift has no dynamic characteristics, , .

[0064] During the calibration process, the variables that need to be iteratively updated are: Kalman gain: .

[0065] Posterior estimate: .

[0066] Update the error covariance matrix: .

[0067] After Kalman filter estimation, the centroid offset is obtained, such as Figure 5 As shown, Figure 5 Given the centroid offset The calibration results and corresponding centroid offsets are recorded as follows: Table 1 - Comparison of the true value of the center of mass offset and the calibration result

[0068] Using the short-period maneuver of the spacecraft (the maneuver duration is 250s), the inertial sensor The calibration result of the axis center of mass offset is as follows: Figure 6 As shown in the figure, the three-axis calibration accuracy of the simulated Taiji-2 center of mass offset is about 10µm.

[0069] In the actual output acceleration of the inertial sensor, the non-conservative force acceleration dominated by solar light pressure is the dominant item with a noise amplitude of 10 -8 ms -2 The magnitude of the maneuvering time window is limited to 250s to maintain the linear characteristics of the non-conservative force, and the linear acceleration readout signal of the inertial sensor is delinearized and compared with the linear acceleration caused by the center of mass offset estimated by the Kalman filter. After the calibration of the center of mass offset is completed, the acceleration noise term coupled with the center of mass offset of the inertial sensor can be identified and eliminated according to the calibration results, thereby reducing the acceleration noise level of the inertial sensor during the calibration period to the inertial sensor background noise.

[0070] In this embodiment, an inertial sensor center of mass offset on-orbit calibration device is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and will not be repeated hereafter. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0071] This embodiment provides an on-orbit calibration device for an inertial sensor mass center offset. Figure 7 As shown, including: An acquisition module 71 is used to obtain the angular velocity and angular acceleration of the spacecraft after the maneuver through the inertial sensor; A construction module 72 is used to construct a metrological observation model using the angular velocity and angular acceleration of the spacecraft; The processing module 73 is used to process the metrology observation model through a pre-built Kalman filter to obtain an estimated centroid offset; The calibration module 74 is used to obtain a calibration result of the mass center offset between the mass center of the inertial sensor and the center of gravity of the spacecraft based on the estimated mass center offset and the acceleration calculation output by the inertial sensor.

[0072] In the embodiment of the present application, the acquisition module 71 is used to detect the attitude signal of the test quality generated by the inertial sensor, wherein the attitude signal is generated by the inertial sensor after the spacecraft maneuvers; and analyze the attitude signal to obtain the angular velocity and angular acceleration of the spacecraft.

[0073] In the embodiment of the present application, the measurement observation model is as follows: .

[0074] in, , The linear term of acceleration as a non-conservative force coupled with the test mass can be treated by eliminating the linear trend.

[0075] In an embodiment of the present application, the processing module 73 is used to obtain the working parameters of the Kalman filter and determine the Kalman filter update equation, wherein the working parameters include state variables, initial state estimates and covariance matrices; preprocess the angular velocity and angular acceleration to obtain processed angular velocity and angular acceleration; initialize the state variables and covariance matrix of the Kalman filter, and use the initialized state variables and the system model to perform predictions to obtain prediction results; compare the preprocessed angular velocity and angular acceleration with the prediction results to obtain comparison results, and use the comparison results to calculate the Kalman gain; use the Kalman gain and the update equation to calculate the updated values ​​of the state variables and the updated values ​​of the covariance matrix; determine the estimated center of mass offset based on the updated values ​​of the state variables and the updated values ​​of the covariance matrix.

[0076] In the embodiment of the present application, the calibration module 74 is used to obtain the acceleration currently actually output by the inertial sensor; perform delinearization trend processing on the acceleration to obtain the processed acceleration; obtain the linear acceleration caused by the estimated center of mass offset; determine the difference between the processed acceleration and the linear acceleration, and determine the actual value of the center of mass offset based on the difference; determine the calibration result of the center of mass offset between the center of mass of the inertial sensor and the center of gravity of the spacecraft based on the actual value of the center of mass offset.

[0077] In an embodiment of the present application, the device also includes: an evaluation module, which is used to collect acceleration data output by the inertial sensor and analyze the acceleration data to obtain a noise analysis result; determine the acceleration noise term coupled with the center of mass offset according to the calibration result of the center of mass offset and the noise analysis result; eliminate or reduce the acceleration noise term in the acceleration data to obtain processed acceleration data, and evaluate the acceleration noise level corresponding to the processed acceleration data; if the acceleration noise level meets the preset conditions, the processed acceleration data is used as output. See also Figure 8 , Figure 8 is a schematic diagram of the structure of an electronic device provided by an optional embodiment of the present invention, such as Figure 8 As shown, the electronic device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process instructions executed in the electronic device, including instructions stored in or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple electronic devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 8 A processor 10 is taken as an example.

[0078] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0079] The memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0080] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created by the use of an electronic device based on the presentation of a small program landing page, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the electronic device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0081] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0082] The electronic device further comprises a communication interface 30 for the electronic device to communicate with other devices or a communication network.

[0083] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0084] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. An on-orbit calibration method for inertial sensor center of mass offset, characterized in that: The inertial sensor is arranged on the spacecraft, and the method comprises: angular velocity and angular acceleration of the spacecraft after the maneuver by the inertial sensor; constructing a metrological observation model using the angular velocity of the spacecraft and the angular acceleration; The measurement observation model is processed by a pre-constructed Kalman filter to obtain an estimated center of mass offset; Based on the estimated center of mass offset and the acceleration calculation output by the inertial sensor, a calibration result of the center of mass offset between the center of mass of the inertial sensor and the center of gravity of the spacecraft is obtained.

2. The method according to claim 1, characterized in that The angular velocity and angular acceleration measured by the inertial sensor after the spacecraft maneuvers include: Detecting an attitude signal of test quality generated by an inertial sensor, wherein the attitude signal is generated by the inertial sensor after the spacecraft maneuvers; The attitude signal is analyzed to obtain the angular velocity and angular acceleration of the spacecraft.

3. The method according to claim 1, characterized in that The measurement observation model is as follows: in, , The linear term of acceleration as a non-conservative force coupled with the test mass can be treated by eliminating the linear trend.

4. The method according to claim 1, characterized in that: The method of processing the metrology observation model by using a pre-built Kalman filter to obtain an estimated centroid shift includes: Acquiring operating parameters of a Kalman filter and determining an update equation of the Kalman filter, wherein the operating parameters include state variables, an initial state estimate, and a covariance matrix; Preprocessing the angular velocity and the angular acceleration to obtain processed angular velocity and angular acceleration; Initialize the state variables and covariance matrix of the Kalman filter, and use the initialized state variables and system model to perform predictions to obtain prediction results; Comparing the preprocessed angular velocity and angular acceleration with the prediction result to obtain a comparison result, and calculating the Kalman gain using the comparison result; Calculating updated values ​​of state variables and updated values ​​of covariance matrix using the Kalman gain and the update equation; An estimated center of mass shift is determined based on the updated values ​​of the state variables and the updated values ​​of the covariance matrix.

5. The method according to claim 4, characterized in that The formula of the Kalman filter is as follows: is the state transfer matrix in the prediction process, is the gain of input U, W is the estimated process noise, and V is the measurement noise, where the measured value Y, the estimated , the observation matrix H is: 。 6. The method according to claim 1, characterized in that The calculating based on the estimated center of mass offset and the acceleration output by the inertial sensor to obtain a calibration result of the center of mass offset between the center of mass of the inertial sensor and the center of gravity of the spacecraft includes: Obtaining the acceleration actually output by the inertial sensor at present; Performing a delinearization trend processing on the acceleration to obtain a processed acceleration; Obtaining the linear acceleration caused by the estimated center of mass deviation; determining a difference between the processed acceleration and the linear acceleration, and determining an actual value of the center of mass shift based on the difference; A calibration result of the mass center offset between the mass center of the inertial sensor and the center of gravity of the spacecraft is determined according to the actual value of the mass center offset.

7. The method according to claim 1, characterized in that The method further comprises: Collecting acceleration data output by the inertial sensor, and analyzing the acceleration data to obtain a noise analysis result; Determining an acceleration noise term coupled with the mass center offset according to the calibration result of the mass center offset and the noise analysis result; Eliminating or reducing acceleration noise items in the acceleration data to obtain processed acceleration data, and evaluating the acceleration noise level corresponding to the processed acceleration data; If the acceleration noise level meets the preset condition, the processed acceleration data is used as output.

8. An on-orbit calibration device for inertial sensor mass center offset, characterized in that: The device comprises: An acquisition module, used for obtaining the angular velocity and angular acceleration of the spacecraft after the maneuver occurs through the inertial sensor; A construction module, used to construct a metrology observation model using the angular velocity of the spacecraft and the angular acceleration; A processing module, used for processing the metrology observation model through a pre-built Kalman filter to obtain an estimated centroid offset; The calibration module is used to obtain a calibration result of the center of mass offset between the center of mass of the inertial sensor and the center of gravity of the spacecraft based on the estimated center of mass offset and the acceleration calculation output by the inertial sensor.

9. An electronic device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 7.

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